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| [[https://www.packtpub.com/big-data-and-business-intelligence/network-science-python-and-networkx-quick-start-guide|Network Science with Python and NetworkX Quick Start Guide]] Edward Platt ISBN 13: 9781789955316 Packt 190 Pages (25 Apr 2019) '''Book Overview:''' Manipulate and analyze network data with the power of Python and NetworkX NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use. With this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems. [[https://www.packtpub.com/big-data-and-business-intelligence/network-science-python-and-networkx-quick-start-guide|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/data-science-projects-python|Data Science Projects with Python]] Steve Klosterman ISBN 13: 9781838551025 Packt 374 Pages (29 Apr 2019) '''Book Overview:''' A case study approach to successful data science projects using Python, pandas, and scikit-learn Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The book will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. With this book, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data. [[https://www.packtpub.com/big-data-and-business-intelligence/data-science-projects-python|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/applied-supervised-learning-python|Applied Supervised Learning with Python]] Benjamin Johnston and Ishita Mathur ISBN 13: 9781789954920 Packt 404 Pages (26 Apr 2019) '''Book Overview:''' Explore the exciting world of machine learning with the fastest growing technology in the world Machine learning—the ability of a machine to give right answers based on input data—has revolutionized the way we do business. Applied Supervised Learning with Python provides a rich understanding of how you can apply machine learning techniques in your data science projects using Python. You'll explore Jupyter Notebooks, the technology used commonly in academic and commercial circles with in-line code running support. With this book, you'll be equipped to not only work with machine learning algorithms, but also be able to create some of your own! [[https://www.packtpub.com/big-data-and-business-intelligence/applied-supervised-learning-python#tab-label-additional|Publisher's page]] ---- [[https://prod.packtpub.com/big-data-and-business-intelligence/hands-unsupervised-learning-python|Hands-On Unsupervised Learning with Python]] Giuseppe Bonaccorso ISBN 13: 9781789348279 Packt 386 Pages (28 Feb 2019) '''Book Overview:''' Discover the skill-sets required to implement various approaches to Machine Learning with Python Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. With this book, you will have learned the art of unsupervised learning for different real-world challenges. [[https://prod.packtpub.com/big-data-and-business-intelligence/hands-unsupervised-learning-python|Publisher's page]] ---- [[https://prod.packtpub.com/big-data-and-business-intelligence/mastering-python-finance-second-edition|Mastering Python for Finance - Second Edition]] James Ma Weiming ISBN 13: 9781789346466 Packt 426 Pages(29 Apr 2019) '''Book Overview:''' Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples. With this book, you will also be able to apply Python to different paradigms in the financial industry and perform efficient data analysis. [[https://prod.packtpub.com/big-data-and-business-intelligence/mastering-python-finance-second-edition|Publisher's page]] ---- [[https://www.packtpub.com/programming/python-parallel-programming-cookbook|Python Parallel Programming Cookbook - Second Edition]] Giancarlo Zaccone ISBN 13: 9781789533736 Packt 370 Pages (6 Sep 2019) '''Book:''' Implement effective programming techniques in Python to build scalable software that saves time and memory This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications. With this book, you will be confident in building concurrent and high-performing applications in Python. [[https://www.packtpub.com/?utm_source=wiki.python&utm_medium=referral&utm_campaign=Outreach|Publisher's page]] ---- [[https://www.packtpub.com/data/hands-on-neuroevolution-with-python?utm_source=wiki.python.org&utm_medium=referral&utm_campaign=OutreachB14532dollar5|Hands-On Neuroevolution with Python]] Iaroslav Omelianenko ISBN 13 :9781838824914 Packt 368 pages (December 24, 2019) '''Book Overview:''' Neuroevolution is a form of artificial intelligence learning that uses evolutionary algorithms to simplify the process of solving complex tasks in domains such as games, robotics, and the simulation of natural processes. This book will give you comprehensive insights into essential neuroevolution concepts and equip you with the skills you need to apply neuroevolution-based algorithms to solve practical, real-world problems. You'll start with learning the key neuroevolution concepts and methods by writing code with Python. You'll also get hands-on experience with popular Python libraries and cover examples of classical reinforcement learning, path planning for autonomous agents, and developing agents to autonomously play Atari games. Next, you'll learn to solve common and not-so-common challenges in natural computing using neuroevolution-based algorithms. Later, you'll understand how to apply neuroevolution strategies to existing neural network designs to improve training and inference performance. Finally, you'll gain clear insights into the topology of neural networks and how neuroevolution allows you to develop complex networks, starting with simple ones. By the end of this book, you will not only have explored existing neuroevolution-based algorithms, but also have the skills you need to apply them in your research and work assignments. [[https://www.packtpub.com/data/hands-on-neuroevolution-with-python?utm_source=wiki.python.org&utm_medium=referral&utm_campaign=OutreachB14532dollar5|Publisher's page]] ---- [[https://www.packtpub.com/data/mastering-pandas-second-edition?/utm_source=python.org&utm_medium=referral&utm_OutreachB11257dollar5|Mastering pandas - Second Edition]] Ashish Kumar ISBN 13: 9781789343236 Packt Course Length: 20 hours 13 minutes (25 Oct 2019) '''Video Overview:''' Perform advanced data manipulation tasks using pandas and become an expert data analyst. pandas is a popular Python library used by data scientists and analysts worldwide to manipulate and analyze their data. This book presents useful data manipulation techniques in pandas to perform complex data analysis in various domains. With this book, you will learn how to perform efficient data analysis using pandas on complex data, and become an expert data analyst or data scientist in the process. [[https://www.packtpub.com/data/mastering-pandas-second-edition?/utm_source=python.org&utm_medium=referral&utm_OutreachB11257dollar5|Publisher's page]] ---- [[https://www.packtpub.com/web-development/python-api-development-fundamentals?utm_source=wiki.python.org&utm_medium=wiki&utm_campaign=OutreachB15308fivedollar|Python API Development Fundamentals]] Jack Huang, Ray Chung, Et al ISBN 13 :9781838983994 Packt 372 Pages (22 Nov 2019) '''Book Overview:''' Learn all that’s needed to build a fully functional web application from scratch. Python is a flexible language that can be used for much more than just script development. By knowing the Python RESTful APIs work, you can build a powerful backend for web applications and mobile applications using Python. You'll take your first steps by building a simple API and learning how the frontend web interface can communicate with the backend. You'll also learn how to serialize and deserialize objects using the marshmallow library. Then, you'll learn how to authenticate and authorize users using Flask-JWT. You'll also learn how to enhance your APIs by adding useful features, such as email, image upload, searching, and pagination. You'll wrap up the whole book by deploying your APIs to the cloud. By the end of this book, you'll have the confidence and skill to leverage the power of RESTful APIs and Python to build efficient web applications. [[https://www.packtpub.com/web-development/python-api-development-fundamentals?utm_source=wiki.python.org&utm_medium=wiki&utm_campaign=OutreachB15308fivedollar|Publisher's page]] ---- [[https://www.packtpub.com/web-development/full-stack-react-python-and-graphql-video?utm_source=Python.org&utm_medium=wikiforum&utm_campaign=OutreachV15708|Full-Stack React, Python, and GraphQL [Video]]] Reed Barger ISBN 13: 9781839215698 Packt Course Length: 6 hours 35 minutes (24 Oct 2019) ''' Video Overview:''' Develop impressive, rich full-stack apps with the latest and greatest features of Python, React, and GraphQL This course is for developers keen to build complete, full-stack applications with cutting-edge React user interfaces, powered by a robust Python backend and using GraphQL on the server and client. This course was designed for developers keen to get ahead of the curve in the latest web technologies, and focuses on how to use GraphQL from front to back, the most current techniques and tools in React (including React Hooks, Apollo Boost, and Material UI), and how to combine it all with Python, Django, and Graphene for an amazing stack. You'll be building a full-stack app from scratch with a GraphQL API made with Python (Django and Graphene); a React client app with React Hooks and Apollo Boost; state management React Context (with useContext) and Apollo Client State, media file uploads with Cloudinary; and tons more. This app will be a social music-sharing app called ReactTracks where users can upload and share any music they like, interact with various tracks by liking them and adding them to their profile, searching for tracks, adding information about their music, and editing/deleting their tracks. [[https://www.packtpub.com/web-development/full-stack-react-python-and-graphql-video?utm_source=Python.org&utm_medium=wikiforum&utm_campaign=OutreachV15708|Publisher's page]] ---- [[https://www.packtpub.com/security/learn-python-and-ethical-hacking-from-scratch-video?utm_source=Python.org&utm_medium=wikiforum&utm_campaign=Outreach V15319|Learn Python and Ethical Hacking from Scratch [Video]]] Zaid Sabih ISBN 13:9781839214561 Packt course Length: 23 hours 29 minutes (11 Oct 2019) '''Video Overview:''' Start from scratch and learn both topics simultaneously by writing 20+ hacking programs This course is highly practical but doesn't neglect the theory, so we start by covering some basics for ethical hacking and Python programming, installing the required software, and then starting to program straightaway. So, by the end of the course, you'll have the programming skills to write any program even if it has nothing to do with hacking, but you'll learn to program by programming hacking tools! All the code files are placed at https://github.com/PacktPublishing/Learn-Python-and-Ethical-Hacking-From-Scratch [[https://www.packtpub.com/security/learn-python-and-ethical-hacking-from-scratch-video?utm_source=Python.org&utm_medium=wikiforum&utm_campaign=Outreach V15319|Publisher's page]] ---- [[https://www.packtpub.com/data/hands-on-reinforcement-learning-algorithms-with-python?utm_source=Python.org&utm_medium=wikiforum&utm_campaign=OutreachB10405|Reinforcement Learning Algorithms with Python]] Andrea Lonza ISBN 13:9781789131116 Packt 366 Pages (18 Oct 2019) '''Book Overview:''' Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behaviour based on changing requirements. This book will help you master RL algorithms and understand their implementation as you build self-learning agents. By the end of the book, you'll have worked with key RL algorithms to overcome challenges in real-world applications and be part of the RL research community. [[https://www.packtpub.com/data/hands-on-reinforcement-learning-algorithms-with-python?utm_source=Python.org&utm_medium=wikiforum&utm_campaign=OutreachB10405|Publisher's page]] ---- [[https://www.packtpub.com/programming/python-a-z-learn-python-programming-by-building-5-projects-video|Python A-Z - Learn Python Programming By Building 5 Projects [Video]]] Shubham Sarda ISBN 13: 9781839212956 Packt Course Length: 12 hours 21 minutes 11 Oct 2019 (MONTH YEAR) '''Video Overview:''' Python programming masterclass for beginners – learn all about Python 3 with object-oriented concepts, five projects and more! Welcome to “Python Programming A-Z – Learn Python Programming by Building Five Projects,” a course that takes you through your Python journey from beginner to advanced step by step. This course touches on every important concept of the latest version of Python, Python 3. Throughout the course, we will explore the most essential Python features: After completing this course, you will be ready to work as an intern, fresher, or freelancer, and you will also be able to implement everything yourself! Most importantly, you will be ready to use the huge scope offered by Python programming. All the codes and supporting files for this course are available at -https://github.com/PacktPublishing/Python-A-Z---Learn-Python-Programming-By-Building-5-Projects [[https://www.packtpub.com/programming/python-a-z-learn-python-programming-by-building-5-projects-video|Publisher's page]] ---- [[https://www.packtpub.com/programming/python-parallel-programming-cookbook?/utm_source=python.org&utm_medium=referral&utm_Outreach|Python Parallel Programming Cookbook - Second Edition]] Giancarlo Zaccone ISBN 13: 9781789533736 Packt 370 pages Pages: 11 hours 6 minutes (6 Sep 2019) '''Book Overview:''' Implement effective programming techniques in Python to build scalable software that saves time and memory Nowadays, it has become extremely important for programmers to understand the link between the software and the parallel nature of their hardware so that their programs run efficiently on computer architectures. Applications based on parallel programming are fast, robust, and easily scalable. This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications. With this book, you will be confident in building concurrent and high-performing applications in Python. [[https://www.packtpub.com/programming/python-parallel-programming-cookbook?/utm_source=python.org&utm_medium=referral&utm_OutreachTITLE URL|Publisher's page]] ---- [[https://www.packtpub.com/programming/python-gui-programming-cookbook-third-edition?/utm_source=python.org&utm_medium=referral&utm_Outreach|Python GUI Programming Cookbook - Third Edition]] Burkhard Meier ISBN 13: 9781838827540 Packt 486 Pages (11 Oct 2019) '''Book Overview:''' Over 90 recipes to help you develop widgets, forms, layouts, charts, and much more using the latest features of Python 3 Python is a multi-domain, interpreted programming language that is easy to learn and implement. With its wide support for frameworks to develop GUIs, you can build interactive and beautiful GUI-based applications easily using Python. This third edition of Python GUI Programming Cookbook follows a task-based approach to help you create effective GUIs with the smallest amount of code. Every recipe in this book builds upon the last to create an entire, real-life GUI application. These recipes also help you solve problems that you might encounter while developing GUIs. This book mainly focuses on using Python’s built-in tkinter GUI framework. You'll learn how to create GUIs in Python using simple programming styles and object-oriented programming (OOP). As you add more widgets and expand your GUI, you will learn how to connect to networks, databases, and graphical libraries that greatly enhance the functionality of your GUI. You’ll also learn how to use threading to ensure that your GUI doesn't become unresponsive. Toward the end, you’ll learn about the versatile PyQt GUI framework, which comes along with its own visual editor that allows you to design GUIs using drag and drop features. By the end of the book, you’ll be an expert in designing Python GUIs and be able to develop a variety of GUI applications with ease. [[https://www.packtpub.com/programming/python-gui-programming-cookbook-third-edition?/utm_source=python.org&utm_medium=referral&utm_Outreach|Publisher's page]] ---- [[https://www.packtpub.com/?utm_source=wiki.python&utm_medium=referral&utm_DataUnlocked|Python GUI Programming - A Complete Reference Guide]] Alan D. Moore and B.M. Harwani ISBN 13: 9781838988470 Packt 746 Pages (24 Jun 2019) '''Book Overview:''' Explore Python’s GUI frameworks and create visually stunning and feature-rich applications This Learning Path begins by introducing you to Tkinter and PyQt, before guiding you through the application development process. As you expand your GUI by adding more widgets, you'll work with networks, databases, and graphical libraries that enhance its functionality. You'll also learn how to connect to external databases and network resources, test your code, and maximize performance using asynchronous programming. In later chapters, you'll understand how to use the cross-platform features of Tkinter and Qt5 to maintain compatibility across platforms. You’ll be able to mimic the platform-native look and feel, and build executables for deployment across popular computing platforms. With this book you'll have the skills and confidence to design and build high-end GUI applications that can solve real-world problems. [[https://www.packtpub.com/programming/python-gui-programming-a-complete-reference-guide|Publisher's page]] ---- [[https://www.packtpub.com/programming/python-clean-coding-video|Python Clean Coding]] Peter Fisher ISBN 13: 9781788831079 Course Length: 2 hours 8 minutes (3 Jul 2019) '''Video Overview:''' Discover simple practices for writing clean and efficient Python code Even bad code can function. But if code isn't clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn't have to be that way. With this course we will apply what we’ve learned in the previous videos to rewriting and reorganizing real-world Python programs into clean and beautiful code that can be more easily understood, debugged, and extended. [[https://www.packtpub.com/programming/python-clean-coding-video|Publisher's page]] ---- [[https://www.packtpub.com/programming/python-gui-programming-a-complete-reference-guide|Python GUI Programming - A Complete Reference Guide]] Alan D. Moore and B.M. Harwani ISBN 13: 9781838988470 Packt 746 Pages Course Length: 22 hours 22 minutes (24 Jun 2019) '''Book:''' Explore Python’s GUI frameworks and create visually stunning and feature-rich applications A responsive graphical user interface (GUI) helps you interact with your application, improves user experience, and enhances the efficiency of your applications. With Python, you’ll have access to elaborate GUI frameworks that you can use to build interactive GUIs that stand apart from the rest. With this book you'll have the skills and confidence to design and build high-end GUI applications that can solve real-world problems. [[https://www.packtpub.com/programming/python-gui-programming-a-complete-reference-guide|Publisher's page]] ---- [[https://www.packtpub.com/application-development/hands-qt-python-developers?utm_source=python-forum.io&utm_medium=referral&utm_campaign=Outreach|Hands-On Qt for Python Developers]] Volodymyr Kirichinets ISBN 13: 9781789612790 Packt 770 Pages (29 May 2019) '''Book Overview:''' Boost UI development with ready-made widgets, controls, charts, and data visualization and create stunning 2D and 3D graphics with PyQt and PySide2. Qt is one of the most widely used and flexible frameworks for GUI application development, allowing you to write your application once and then deploy it to multiple operating systems. This book combines the best of Python and Qt to help you develop GUI applications with Python bindings, such as PyQt and PySide, that will supercharge your Python applications. With this book, you will be able to create modern, responsive, cross-platform desktop applications with the power of Qt, Python, and QML. [[https://www.packtpub.com/application-development/hands-qt-python-developers?utm_source=python-forum.io&utm_medium=referral&utm_campaign=Outreach|Publisher's page]] ---- [[https://www.packtpub.com/application-development/deep-learning-and-neural-networks-using-python-keras-complete-beginners-guid|Deep Learning and Neural Networks using Python - Keras: The Complete Beginners Guide ]] Abilash Nelson ISBN 13: 9781838986476 Packt Course Length: 11 hours 7 minutes (28 May 2019) '''Video Overview:''' Deep learning and data science using a Python and Keras library - The complete guide from a beginner to professional The world has been obsessed with the terms "machine learning" and "deep learning" recently. We use these technologies every day, with or without our knowledge. Ranging from Google suggestions to translations, ads, movie recommendations, friend suggestions, sales and customer experiences. There are tons of other applications too so there’s no wonder that deep learning and machine learning specialists, along with data science practitioners, are the most sought-after talent in the current technology world. But the problem is that, when you think about learning these technologies, there is a common misconception that it’s a prerequisite to study lots of maths, statistics, and complex algorithms. It’s almost like someone making you believe that you must learn the working of an internal combustion engine before you learn how to drive a car This course is organized and an overview of the list of topics included. Overall, this is a basic to an advanced crash course in deep learning neural networks and convolutional neural networks using Keras and Python. [[https://www.packtpub.com/application-development/deep-learning-and-neural-networks-using-python-keras-complete-beginners-guid|Publisher's page]] ---- [[https://www.packtpub.com/application-development/using-mysql-databases-python-video|Using MySQL Databases With Python]] John Elder ISBN 13: 9781838984670 Packt Course Length: 2 hours 2 minutes (28 May 2019) '''Video Overview:''' Learn the MySql Database with Python the fast and easy way! These days, everything uses a database, and MySQL is one of the most popular databases out there. FREE and Open Source, Mysql is a great database for just about all of your needs. Likewise, Python is one of the most popular and powerful programming languages today. Pairing the two together is a powerful combination! With this course, you'll learn the basics of using MySQL with Python. You'll learn how to create databases and tables, add data, sort data, create reports, pull specific data, and more. [[https://www.packtpub.com/application-development/using-mysql-databases-python-video|Publisher's page]] ---- |
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| ---- [[https://www.packtpub.com/big-data-and-business-intelligence/natural-language-processing-fundamentals|Natural Language Processing Fundamentals]] Sohom Ghosh, Dwight Gunning ISBN 13: 9781789954043 Packt 374 Pages (March 2019) '''Book Overview:''' Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals.The book will easily equip you with the knowledge you need to build applications that interpret human language. [[https://www.packtpub.com/big-data-and-business-intelligence/natural-language-processing-fundamentals|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/deep-learning-pytorch-quick-start-guide|Deep Learning with PyTorch Quick Start Guide]] David Julian ISBN 13: 9781789534092 Packt 118 pages (December 2018) '''Book Overview:''' PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. [[http://www.amazon.com/dp/1789534097|Amazon Page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/machine-learning-fundamentals|Machine Learning Fundamentals]] Hyatt Saleh ISBN 13: 9781789803556 Packt 240 Pages (November 2018) '''Book Overview:''' With the flexibility and features of scikit-learn and Python, build machine learning algorithms that optimize the programming process and take application performance to a whole new level As machine learning algorithms become popular, new tools that optimize these algorithms are also developed. Machine Learning Fundamentals explains you how to use the syntax of scikit-learn. You'll study the difference between supervised and unsupervised models, as well as the importance of choosing the appropriate algorithm for each dataset. You'll apply unsupervised clustering algorithms over real-world datasets, to discover patterns and profiles, and explore the process to solve an unsupervised machine learning problem. The focus of the book then shifts to supervised learning algorithms. You'll learn to implement different supervised algorithms and develop neural network structures using the scikit-learn package. You'll also learn how to perform coherent result analysis to improve the performance of the algorithm by tuning hyperparameters. [[https://www.packtpub.com/big-data-and-business-intelligence/machine-learning-fundamentals|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/python-fundamentals|Python Fundamentals]] Ryan Marvin, Mark Ng’ang’a, Amos Omondi ISBN 13: 9781789807325 Packt 324 Pages (October 2018) '''Book Overview:''' With an interesting mix of theory and practicals, explore Python and its features, and progress from beginner to being skilled in this popular scripting language As you settle into the Python ecosystem, you'll learn about data structures and study ways to correctly store and represent information. By working through specific examples, you'll learn how Python implements object-oriented programming (OOP) concepts of abstraction, encapsulation of data, inheritance, and polymorphism. You'll be given an overview of how imports, modules, and packages work in Python, how you can handle errors to prevent apps from crashing, as well as file manipulation. By the end of this book, you'll have built up an impressive portfolio of projects and armed yourself with the skills you need to tackle Python projects in the real world. [[https://www.packtpub.com/big-data-and-business-intelligence/python-fundamentals|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/python-data-science-essentials-third-edition|Python Data Science Essentials - Third Edition]] Alberto Boschetti, Luca Massaron ISBN 13: 9781789537864 Packt 472 pages(September 2018) '''Book Overview:''' Gain useful insights from your data using popular data science tools Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn. The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You’ll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost. By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users. [[https://www.packtpub.com/big-data-and-business-intelligence/python-data-science-essentials-third-edition|Publisher's page]] ---- [[https://www.amazon.com/Python-Artificial-Intelligence-Projects-Beginners/dp/1789539463/|Python Artificial Intelligence Projects for Beginners]] Joshua Eckroth ISBN 13: 9781789539462 Packt 162 Pages '''Book Overview:''' This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library. By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress. [[https://www.packtpub.com/big-data-and-business-intelligence/python-artificial-intelligence-projects-beginners|Publisher's page]] ---- Samuel Bowne ISBN 13: 9781789534443 Packt 100 Pages '''Book Overview:''' Learn to evaluate and compare data encryption methods and attack cryptographic systems Cryptography is essential for protecting sensitive information, but it is often performed inadequately or incorrectly. Hands-On Cryptography with Python starts by showing you how to encrypt and evaluate your data. The book will then walk you through various data encryption methods,such as obfuscation, hashing, and strong encryption, and will show how you can attack cryptographic systems. You will learn how to create hashes, crack them, and will understand why they are so different from each other. In the concluding chapters, you will use three NIST-recommended systems: the Advanced Encryption Standard (AES), the Secure Hash Algorithm (SHA), and the Rivest-Shamir-Adleman (RSA). By the end of this book, you will be able to deal with common errors in encryption. [[https://www.packtpub.com/networking-and-servers/hands-cryptography-python|Publisher's page]] ---- [[https://www.amazon.com/Hands-Data-Analysis-NumPy-pandas-ebook/dp/B07F7FLWKM/|Hands-On Data Analysis with NumPy and Pandas]] Curtis Miller ISBN 13: 9781789530797 Packt 168 Pages (June 2018) '''Book Overview:''' Get to grips with the most popular Python packages that make Data Analysis possible Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation. [[https://www.packtpub.com/big-data-and-business-intelligence/hands-data-analysis-numpy-and-pandas|Publisher's page]] ---- [[https://www.amazon.com/dp/1788834240|Deep Reinforcement Learning Hands-On]] Maxim Lapan ISBN 13: 9781788834247 Packt 546 Pages (June 2018) '''Book Overview:''' This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. Recent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google’s use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace. Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on ‘grid world’ environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots. [[https://www.packtpub.com/big-data-and-business-intelligence/deep-reinforcement-learning-hands|Publisher's page]] ---- [[https://www.amazon.com/dp/1788831101|Deep Learning with TensorFlow]] Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy ISBN 13: 9781786469786 Packt 320 Pages (April 2018) '''Book Overview:''' Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide. Throughout the book, you’ll learn how to implement deep learning algorithms for machine learning systems and integrate them into your product offerings, including search, image recognition, and language processing. Additionally, you’ll learn how to analyze and improve the performance of deep learning models. This can be done by comparing algorithms against benchmarks, along with machine intelligence, to learn from the information and determine ideal behaviors within a specific context. After finishing the book, you will be familiar with machine learning techniques, in particular the use of TensorFlow for deep learning, and will be ready to apply your knowledge to research or commercial projects. [[https://www.packtpub.com/big-data-and-business-intelligence/deep-learning-tensorflow|Publisher's page]] ---- [[https://www.amazon.com/Hands-Transfer-Learning-Python-TensorFlow/dp/1788831306/|Hands-On Transfer Learning with Python]] Dipanjan Sarkar, Raghav Bali, Tamoghna Ghosh ISBN 13: 9781788831307 Packt 438 Pages (August 2018) '''Book Overview:''' Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples. The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with practical examples. In the concluding chapters, we will focus on a multitude of real-world case studies and problems associated with areas such as computer vision, audio analysis and natural language processing (NLP). [[https://www.packtpub.com/big-data-and-business-intelligence/hands-transfer-learning-python|Publisher's page]] ---- [[https://www.packtpub.com/application-development/mastering-python-design-patterns-second-edition|Mastering Python Design Patterns - Second Edition]] Kamon Ayeva, Sakis Kasampalis ISBN 13: 9781788837484 Packt 248 Pages (August 2018) '''Book Overview:''' Exploit various design patterns to master the art of solving problems using Python This book takes you through a variety of design patterns and explains them with real-world examples. You will get to grips with low-level details and concepts that show you how to write Python code, without focusing on common solutions as enabled in Java and C++. You'll also fnd sections on corrections, best practices, system architecture, and its designing aspects. This book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems. You'll focus on most of the Gang of Four (GoF) design patterns, which are used to solve everyday problems, and take your skills to the next level with reactive and functional patterns that help you build resilient, scalable, and robust applications. By the end of the book, you'll be able to effciently address commonly faced problems and develop applications, and also be comfortable working on scalable and maintainable projects of any size. [[https://www.packtpub.com/application-development/mastering-python-design-patterns-second-edition|Publisher's page]] ---- [[https://www.amazon.com/dp/1788837460|Tkinter GUI Application Development Blueprints, Second Edition]] Bhaskar Chaudhary ISBN 13: 9781788837460 Packt 422 Pages (March 2018) '''Book Overview:''' Geometry Management, Event Handling, and more This book will help you master the art of GUI programming. It delivers the bigger picture of GUI programming by building real-world, productive, and fun applications such as a text editor, drum machine, game of chess, audio player, drawing application, piano tutor, chat application, screen saver, port scanner, and much more. In every project, you will build on the skills acquired in the previous project and gain more expertise. You will learn to write multithreaded programs, network programs, database-driven programs, asyncio based programming and more. You will also get to know the modern best practices involved in writing GUI apps. With its rich source of sample code, you can build upon the knowledge gained with this book and use it in your own projects in the discipline of your choice. [[https://www.packtpub.com/application-development/tkinter-gui-application-development-blueprints-second-edition|Publisher's page]] ---- [[https://www.amazon.com/dp/1788622308|Tkinter GUI Application Development Cookbook]] Alejandro Rodas de Paz ISBN 13: 9781788622301 Packt 242 Pages (March 2018) '''Book Overview:''' Discover solutions to all your Tkinter and Python GUI development problems As one of the more versatile programming languages, Python is well-known for its batteries-included philosophy, which includes a rich set of modules in its standard library; Tkinter is the library included for building desktop applications. Due to this, Tkinter is a common choice for rapid GUI development, and more complex applications can benefit from the full capabilities of this library. This book covers all of your Tkinter and Python GUI development problems and solutions. Tkinter GUI Application Development Cookbook starts with an overview of Tkinter classes and at the same time provides recipes for basic topics, such as layout patterns and event handling. Next, we cover how to develop common GUI patterns, such as entering and saving data, navigating through menus and dialogs, and performing long-running actions in the background.You can then make your apps leverage network resources effectively and perform graphical operations on a canvas and related tasks such as detecting collisions between items. Finally, this book covers using themed widgets, an extension of Tk widgets that have a more native look and feel. Finally, this book covers using the canvas and themed widgets. [[https://www.packtpub.com/web-development/tkinter-gui-application-development-cookbook|Publisher's page]] ---- [[https://www.amazon.com/dp/1788399080|Python Interviews]] Mike Driscoll ISBN 13: 9781788399081 Packt 366 Pages (February 2018) '''Book Overview:''' Mike Driscoll takes you on a journey talking to a hall-of-fame list of truly remarkable Python experts. You'll be inspired every time by their passion for the Python language, as they share with you their experiences, contributions, and careers in Python. Hear from these key Python thinkers about the current status of Python, and where it's heading in the future. Listen to their close thoughts on significant Python topics, such as Python's role in scientific computing, and machine learning. Understand the direction of Python, and what needs to change for Python 4 Each of these twenty Python Interviews can inspire and refresh your relationship with Python and the people who make Python what it is today. Let these interviews spark your own creativity, and discover how you also have the ability to make your mark on a thriving tech community. This book invites you to immerse in the Python landscape, and let these remarkable programmers show you how you too can connect and share with Python programmers around the world. Learn from their opinions, enjoy their stories, and use their tech tips. [[https://www.packtpub.com/web-development/python-interviews|Publisher's page]] ---- [[https://www.amazon.com/dp/1788396901|OpenCV 3.x with Python By Example - Second Edition]] Gabriel Garrido, Prateek Joshi ISBN 13: 9781788396905 Packt 268 Pages (January 2018) '''Book:''' Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications. [[https://www.packtpub.com/application-development/opencv-3x-python-example-second-edition|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/scikit-learn-cookbook-second-edition|scikit-learn Cookbook - Second Edition]] Julian Avila, Trent Hauck ISBN 13: 9781787286382 Packt 374 Pages (November 2017) '''Book Overview:''' Learn to use scikit-learn operations and functions for Machine Learning and deep learning applications. This book includes walk throughs and solutions to the common as well as the not-so-common problems in machine learning, and how scikit-learn can be leveraged to perform various machine learning tasks effectively. [[https://www.packtpub.com/big-data-and-business-intelligence/scikit-learn-cookbook-second-edition|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/pandas-cookbook|Pandas Cookbook]] Theodore Petrou ISBN 13: 9781784393878 Packt 538 Pages (October 2017) '''Book Overview:''' Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysis This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. [[https://www.packtpub.com/big-data-and-business-intelligence/pandas-cookbook|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/python-deep-learning-cookbook|Python Deep Learning Cookbook]] Indra den Bakker ISBN 13: 9781787125193 Packt 330 Pages (October 2017) '''Book Overview:''' Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics. The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras and CNTK is provided. The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios. [[https://www.packtpub.com/big-data-and-business-intelligence/python-deep-learning-cookbook|Publisher's page]] ---- [[https://www.packtpub.com/networking-and-servers/python-digital-forensics-cookbook|Python Digital Forensics Cookbook]] Preston Miller, Chapin Bryce ISBN 13: 9781783987467 Packt Publishing 412 Pages (September 2017) '''Book Overview:''' Over 60 recipes to help you learn digital forensics and leverage Python scripts to amplify your examinations. By leveraging the Python recipes explored throughout this book, you make the complex simple, quickly extracting relevant information from large datasets. You will explore, develop, and deploy Python code and libraries to provide meaningful results that can be immediately applied to your investigations. Throughout the Python Digital Forensics Cookbook, recipes include topics such as working with forensic evidence containers, parsing mobile and desktop operating system artifacts, extracting embedded metadata from documents and executables, and identifying indicators of compromise. You will also learn to integrate scripts with Application Program Interfaces (APIs) such as VirusTotal and PassiveTotal, and tools such as Axiom, Cellebrite, and EnCase. By the end of the book, you will have a sound understanding of Python and how you can use it to process artifacts in your investigations. [[https://www.packtpub.com/networking-and-servers/python-digital-forensics-cookbook|Publisher's page]] ---- ---- [[https://www.packtpub.com/big-data-and-business-intelligence/practical-time-series-analysis|Practical Time Series Analysis]] Dr. Avishek Pal, Dr. PKS Prakash ISBN 13: 9781788290227 Packt Publishing 244 Pages (September 2017) '''Book Overview:''' Step by Step guide filled with real world practical examples. The book starts with descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, you shift focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented, to develop accurate forecasting models for complex time series, and under the availability of little domain knowledge. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python. The book concludes with the Appendix, with a brief discussion of programming and solving data science problems using Python. [[https://www.packtpub.com/big-data-and-business-intelligence/practical-time-series-analysis|Publisher's page]] ---- [[https://www.packtpub.com/application-development/computer-vision-python-3|Computer Vision with Python 3]] Saurabh Kapur ISBN 13: 9781788299763 Packt Publishing 206 Pages (August 2017) '''Book Overview:''' Unleash the power of computer vision with Python to carry out image processing and computer vision techniques This book is a thorough guide for developers who want to get started with building computer vision applications using Python 3. The book is divided into five sections: The Fundamentals of Image Processing, Applied Computer Vision, Making Applications Smarter,Extending your Capabilities using OpenCV, and Getting Hands on. Throughout this book, three image processing libraries Pillow, Scikit-Image, and OpenCV will be used to implement different computer vision algorithms. [[https://www.packtpub.com/application-development/computer-vision-python-3|Publisher's page]] ---- [[https://www.packtpub.com/application-development/learning-concurrency-python|Learning Concurrency in Python]] Elliot Forbes ISBN 13: 9781787285378 Packt Publishing 313 Pages(August 2017) '''Book Overview:''' Practically and deeply understand concurrency in Python to write efficient programs This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems. [[https://www.packtpub.com/application-development/learning-concurrency-python|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/learning-pandas-second-edition|Learning pandas - Second Edition]] Michael Heydt ISBN 13: 9781787123137 Packt Publishing 446 pages (June 2017) '''Book Overview:''' With this book you will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance. With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science. '''What you will learn:''' * Understand how data analysts and scientists think about of the processes of gathering and understanding data * Learn how pandas can be used to support the end-to-end process of data analysis * Use pandas Series and DataFrame objects to represent single and multivariate data * Slicing and dicing data with pandas, as well as combining, grouping, and aggregating data from multiple sources * How to access data from external sources such as files, databases, and web services * Represent and manipulate time-series data and the many of the intricacies involved with this type of data * How to visualize statistical information * How to use pandas to solve several common data representation and analysis problems within finance [[https://www.packtpub.com/big-data-and-business-intelligence/learning-pandas-second-edition|Publisher's page]] ---- [[https://www.packtpub.com/application-development/python-gui-programming-cookbook-second-edition|Python GUI Programming Cookbook - Second Edition]] Burkhard A. Meier ISBN 13: 9781787129450 Packt Publishing 422 pages (May 2017) '''Book Overview:''' This book will guide you through the very basics of creating a fully functional GUI in Python with only a few lines of code. Each and every recipe adds more widgets to the GUIs we are creating. While the cookbook recipes all stand on their own, there is a common theme running through all of them. '''What you will learn:''' * Create the GUI Form and add widgets * Arrange the widgets using layout managers * Use object-oriented programming to create GUIs * Create Matplotlib charts * Use threads and talking to networks * Talk to a MySQL database via the GUI * Perform unit-testing and internationalizing the GUI * Extend the GUI with third-party graphical libraries * Get to know the best practices to create GUIs '''Who this book is written for:''' This book is for intermediate Python programmers who wish to enhance their Python skills by writing powerful GUIs in Python. As Python is such a great and easy to learn language, this book is also ideal for any developer with experience of other languages and enthusiasm to expand their horizon. [[https://www.packtpub.com/application-development/python-gui-programming-cookbook-second-edition|Publisher's page]] ---- [[https://www.packtpub.com/application-development/python-data-structures-and-algorithms|Python Data Structures and Algorithms]] Benjamin Baka ISBN 13: 9781786467355 Packt Publishing 310 pages (May 2017) '''Book Overview:''' In this book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. '''What you will learn:''' * Gain a solid understanding of Python data structures. * Build sophisticated data applications. * Understand the common programming patterns and algorithms used in Python data science. * Write efficient robust code. '''Who this book is written for:''' This book will appeal to all Python developers. A basic knowledge of Python is expected. [[https://www.packtpub.com/application-development/python-data-structures-and-algorithms|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/python-end-end-data-analysis|Python: End-to-end Data Analysis]] Phuong Vothihong, Martin Czygan, Ivan Idris, Magnus Vilhelm Persson & Luiz Felipe Martins ISBN 13: 9781788394697 Packt Publishing 931 pages (May 2017) '''Book Overview:''' This book will get you started with Python data analysis by introducing the basics of data analysis and supported Python libraries such as matplotlib, NumPy, and pandas. Create visualizations by choosing color maps, different shapes, sizes, and palettes then delve into statistical data analysis using distribution algorithms and correlations. '''What you will learn:''' * Understand the importance of data analysis and master its processing steps * Get comfortable using Python and its associated data analysis libraries such as Pandas, NumPy, and SciPy * Clean and transform your data and apply advanced statistical analysis to create attractive visualizations * Analyze images and time series data * Mine text and analyze social networks * Perform web scraping and work with different databases, Hadoop, and Spark * Use statistical models to discover patterns in data * Detect similarities and differences in data with clustering * Work with Jupyter Notebook to produce publication-ready figures to be included in reports '''Who this book is written for:''' This course is for developers, analysts, and data scientists who want to learn data analysis from scratch. This course will provide you with a solid foundation from which to analyze data with varying complexity. A working knowledge of Python (and a strong interest in playing with your data) is recommended. [[https://www.packtpub.com/big-data-and-business-intelligence/python-end-end-data-analysis|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/python-machine-learning-example|Python Machine Learning By Example]] Yuxi (Hayden) Liu ISBN 13: 9781783553112 Packt Publishing 254 pages (May 2017) '''Book Overview:''' This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. '''What you will learn:''' * Exploit the power of Python to handle data extraction, manipulation, and exploration techniques * Use Python to visualize data spread across multiple dimensions and extract useful features * Dive deep into the world of analytics to predict situations correctly * Implement machine learning classification and regression algorithms from scratch in Python * Be amazed to see the algorithms in action * Evaluate the performance of a machine learning model and optimize it * Solve interesting real-world problems using machine learning and Python as the journey unfolds '''Who this book is written for:''' This book is for anyone interested in entering the data science stream with machine learning. Basic familiarity with Python is assumed. [[https://www.packtpub.com/big-data-and-business-intelligence/python-machine-learning-example|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/python-deep-learning|Python Deep Learning]] Valentino Zocca, Gianmario Spacagna, Daniel Slater, Peter Roelants ISBN 13: 9781786464453 Packt Publishing 406 pages (April 2017) '''Book Overview:''' The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results. '''What you will learn:''' * Get a practical deep dive into deep learning algorithms * Explore deep learning further with Theano, Caffe, Keras, and TensorFlow * Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines * Dive into Deep Belief Nets and Deep Neural Networks * Discover more deep learning algorithms with Dropout and Convolutional Neural Networks * Get to know device strategies so you can use deep learning algorithms and libraries in the real world '''Who this book is written for:''' This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired. [[https://www.packtpub.com/big-data-and-business-intelligence/python-deep-learning|Publisher's page]] ---- [[https://www.packtpub.com/application-development/software-architecture-python|Software Architecture with Python]] Anand Balachandran Pillai ISBN 13: 9781786468529 Packt Publishing 556 pages (April 2017) '''Book Overview:''' This book starts off by explaining how Python fits into an application architecture. As you move along, you will understand the architecturally significant demands and how to determine them. Later, you’ll get a complete understanding of the different architectural quality requirements that help an architect to build a product that satisfies business needs, such as maintainability/reusability, testability, scalability, performance, usability, and security. '''What you will learn:''' * Build programs with the right architectural attributes * Use Enterprise Architectural Patterns to solve scalable problems on the Web * Understand design patterns from a Python perspective * Optimize the performance testing tools in Python * Deploy code in remote environments or on the Cloud using Python * Secure architecture applications in Python '''Who this book is written for:''' This book is for experienced Python developers who are aspiring to become the architects of enterprise-grade applications or software architects who would like to leverage Python to create effective blueprints of applications. [[https://www.packtpub.com/application-development/software-architecture-python|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/learning-data-mining-python-second-edition|Learning Data Mining with Python - Second Edition]] Robert Layton ISBN 13: 9781787126787 Packt Publishing 358 pages (April 2017) '''Book Overview:''' This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. '''What you will learn:''' * Apply data mining concepts to real-world problems * Predict the outcome of sports matches based on past results * Determine the author of a document based on their writing style * Use APIs to download datasets from social media and other online services * Find and extract good features from difficult datasets * Create models that solve real-world problems * Design and develop data mining applications using a variety of datasets * Perform object detection in images using Deep Neural Networks * Find meaningful insights from your data through intuitive visualizations * Compute on big data, including real-time data from the internet '''Who this book is written for:''' If you are a Python programmer who wants to get started with data mining, then this book is for you. If you are a data analyst who wants to leverage the power of Python to perform data mining efficiently, this book will also help you. No previous experience with data mining is expected. [[https://www.packtpub.com/big-data-and-business-intelligence/learning-data-mining-python-second-edition|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/python-data-analysis-second-edition|Python Data Analysis - Second Edition]] Armando Fandango ISBN 13: 9781787127487 Packt Publishing 330 pages (March 2017) '''Book Overview:''' With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. '''What you will learn:''' * Install open source Python modules such NumPy, SciPy, Pandas, stasmodels, scikit-learn,theano, keras, and tensorflow on various platforms * Prepare and clean your data, and use it for exploratory analysis * Manipulate your data with Pandas * Retrieve and store your data from RDBMS, NoSQL, and distributed filesystems such as HDFS and HDF5 * Visualize your data with open source libraries such as matplotlib, bokeh, and plotly * Learn about various machine learning methods such as supervised, unsupervised, probabilistic, and Bayesian * Understand signal processing and time series data analysis * Get to grips with graph processing and social network analysis '''Who this book is written for:''' This book is for programmers, scientists, and engineers who have the knowledge of Python and know the basics of data science. It is for those who wish to learn different data analysis methods using Python 3.5 and its libraries. This book contains all the basic ingredients you need to become an expert data analyst. [[https://www.packtpub.com/big-data-and-business-intelligence/python-data-analysis-second-edition|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/python-data-analytics-and-visualization|Python: Data Analytics and Visualization]] Phuong Vo.T.H, Martin Czygan, Ashish Kumar, Kirthi Raman ISBN 13: 9781788290098 Packt Publishing 866 pages (March 2017) '''Book Overview:''' Data analysis is the process of applying logical and analytical reasoning in order to study each data component. Python's powerful standard libraries or toolkits, such as Pylearn2 and Hebel, offer a fast, reliable, cross-platform environment for data analytics. This learning path will start with basic data analysis and you will then will gradually move on to increasingly complex problems; your journey will end with representing analyzed data in meaningful visualizations. '''What you will learn:''' * Get acquainted with NumPy and use arrays and array-oriented computing in data analysis * Process and analyze data using the time-series capabilities of Pandas * Understand the statistical and mathematical concepts behind predictive analytics algorithms * Data visualization with Matplotlib * Interactive plotting with NumPy, Scipy, and MKL functions * Build financial models using Monte-Carlo simulations * Create directed graphs and multi-graphs * Advanced visualization with D3 '''Who this book is written for:''' This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. [[https://www.packtpub.com/big-data-and-business-intelligence/python-data-analytics-and-visualization|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/artificial-intelligence-python|Artificial Intelligence with Python]] Prateek Joshi ISBN 13: 9781786464392 Packt Publishing 446 pages (January 2017) '''Book Overview:''' Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that’s based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! '''What you will learn:''' * Realize different classification and regression techniques * Understand the concept of clustering and how to use it to automatically segment data * See how to build an intelligent recommender system * Understand logic programming and how to use it * Build automatic speech recognition systems * Understand the basics of heuristic search and genetic programming * Develop games using Artificial Intelligence * Learn how reinforcement learning works * Discover how to build intelligent applications centered on images, text, and time series data * See how to use deep learning algorithms and build applications based on it '''Who this book is written for:''' This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. [[https://www.packtpub.com/big-data-and-business-intelligence/artificial-intelligence-python|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/building-recommendation-engines|Building Recommendation Engines]] Suresh Kumar Gorakala ISBN 13: 9781785884856 Packt Publishing 372 pages (December 2016) '''Book Overview:''' The book starts with an introduction to recommendation systems and its applications. You will then start building recommendation engines straight away from the very basics. As you move along, you will learn to build recommender systems with popular frameworks such as R, Python, Spark, Neo4j, and Hadoop. You will get an insight into the pros and cons of each recommendation engine and when to use which recommendation to ensure each pick is the one that suits you the best. '''What you will learn:''' * Build your first recommendation engine * Discover the tools needed to build recommendation engines * Dive into the various techniques of recommender systems such as collaborative, content-based, and cross-recommendations * Create efficient decision-making systems that will ease your work * Familiarize yourself with machine learning algorithms in different frameworks * Master different versions of recommendation engines from practical code examples * Explore various recommender systems and implement them in popular techniques with R, '''Who this book is written for:''' This book caters to beginners and experienced data scientists looking to understand and build complex predictive decision-making systems, recommendation engines using R, Python, Spark, Neo4j, and Hadoop. [[https://www.packtpub.com/big-data-and-business-intelligence/building-recommendation-engines|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python|Bayesian Analysis with Python]] Osvaldo Martin ISBN 13: 9781785883804 Packt Publishing 284 pages (November 2016) '''Book Overview:''' The purpose of this book is to teach the main concepts of Bayesian data analysis. You will learn how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, to check models and validate them. This book begins presenting the key concepts of the Bayesian framework and the main advantages of this approach from a practical point of view. Moving on, you will explore the power and flexibility of generalized linear models and how to adapt them to a wide array of problems, including regression and classification. You will also look into mixture models and clustering data, and you will finish with advanced topics like non-parametrics models and Gaussian processes. With the help of Python and PyMC3 you will learn to implement, check and expand Bayesian models to solve data analysis problems. * Understand the essentials Bayesian concepts from a practical point of view * Learn how to build probabilistic models using the Python library PyMC3 * Acquire the skills to sanity-check your models and modify them if necessary * Add structure to your models and get the advantages of hierarchical models * Find out how different models can be used to answer different data analysis questions * When in doubt, learn to choose between alternative models. * Predict continuous target outcomes using regression analysis or assign classes using logistic and softmax regression. * Learn how to think probabilistically and unleash the power and flexibility of the Bayesian framework '''Who this book is written for:''' Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement probabilistic models in their day to day projects. Programming experience with Python is essential. No previous statistical knowledge is assumed. [[https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python|Publisher's page]] ---- [[https://www.packtpub.com/big-data-and-business-intelligence/python-real-world-machine-learning|Python: Real World Machine Learning]] By Prateek Joshi et al. ISBN 13: 9781787123212 Packt Publishing 941 pages (November 2016) '''Course Overview:''' In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms. The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you’ll acquire a broad set of powerful skills in the area of feature selection and feature engineering. The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python. This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: * Python Machine Learning Cookbook by Prateek Joshi * Advanced Machine Learning with Python by John Hearty * Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca Massaron '''What you learn:''' * Use predictive modeling and apply it to real-world problems * Understand how to perform market segmentation using unsupervised learning * Apply your new-found skills to solve real problems, through clearly-explained code for every technique and test * Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms * Increase predictive accuracy with deep learning and scalable data-handling techniques * Work with modern state-of-the-art large-scale machine learning techniques * Learn to use Python code to implement a range of machine learning algorithms and techniques '''Who this course is for:''' This Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected. [[https://www.packtpub.com/big-data-and-business-intelligence/python-real-world-machine-learning|Publisher's page]] ---- ---- '''Coffee Break Python: 50 Workouts to Kickstart Your Rapid Code Understanding in Python''' By Christian Mayer, September 2018, 191 pages ISBN-13: 978-1719846585 [[http://viewbook.at/CoffeeBreakPython|Coffee Break Python: 50 Workouts to Kickstart Your Rapid Code Understanding in Python]] '''Little time to learn Python? This book shows you how to learn Python during your coffee break!''' Coffee Break Python is a new step-by-step learning system where you repeatedly solve practical Python puzzles. Educational research shows that practical low-stake puzzles and tests help you to learn faster, smarter, and better. As you work through Coffee Break Python, your Python expertise will grow—one coffee at a time. The book is packed with 50 Python puzzles, 10 practical learning tips, 5 compressed cheat sheets, and 1 new way to measure your coding skills. You will train wildly important Python topics such as * Arithmetic operations: integer & float division, and modular arithmetic; * Language elements: branching, loops, keywords, and functions; * Data structures: integer, float, string, list, set, dictionary, and graph; * Sequence operators: indexing, concatenation, slicing, and built-in functions; * Function *arguments: default *, arbitrary *, unpacking *, keyword *; * Set operations: lambda, filter, map, and intersection functions; and * Algorithms: recursion, Fibonacci, matrix search, bubble sort, quick sort, lexicographical sort, guess & check, binary search, and graph traversal. '''How good are your Python skills?''' As a bonus, you will track your individual Python coding skill level throughout the book. This book is for you, if you are slightly beyond beginner-level in Python: * Do you already have experience with another programming language—and now it’s time to tackle Python? * Are you a professional engineer and want to brush up your Python skills? * Are you a student and need to get better at Python for academic courses? [[http://viewbook.at/CoffeeBreakPython|Get the book!]] ---- '''Introduction to Computer Science Using Python: A Computational Problem-Solving Focus''' By Charles Dierbach, John Wiley & Sons, December 2012, 612 pages ISBN 13: 978-0-470-55515-6 '''''Recommended by Guido van Rossum''''' "This is not your average Python book ... The book is incredibly thorough: there are exercises throughout the text (not just at the end of each chapter), and it includes a plethora of examples, screenshots, tables, charts, diagrams, and photos ... I love the final chapter, which is an overview of the history of computing, starting with Charles Babbage and Ada Lovelace ... All in all, I think this book is a great text for anyone teaching CS1." [[http://neopythonic.blogspot.com/2013/10/book-review-charles-dierbach.html|Neopythonic]] '''''Recommended by Textbook Adopter Herbert Daly - University of Bedfordshire''''' "As a University lecturer with considerable responsibility at level 1, I found this book to be an outstanding introduction to the world of computing and the Python language." [[http://www.amazon.co.uk/product-reviews/0470555157/ref=dp_top_cm_cr_acr_txt?ie=UTF8&showViewpoints=1|Amazon Review]] Features: * Basics first approach * Focus on computational problem solving, starting with Chapter 1 * Hands-on "Let's Try It" sections and self-test questions throughout the book * Each chapter section contains a "Let's Apply It" example program * Each chapter ends with the step-by-step development and demonstrated debugging techniques of a significant-size program * Contains various end-of-chapter exercises and assignments, including simple programming exercises, assignments involving the modification of programs from within the chapter, and challenging program development problems * Thirty-four page final chapter on the history of computing, starting with Charles Babbage, with over 65 historical images * Python 3 Programmers' Reference at the end of the book for quick look-up of Python details PROVIDED INSTRUCTOR MATERIALS: * instructors' manual (with answers to chapter exercises and assignments) * source code for all textbook examples * solution code for program assignments * over 1,000 well-designed, PowerPoint slides, including every fundamental aspect of each chapter * included test bank [[http://www.wiley.com/WileyCDA/WileyTitle/productCd-EHEP002046.html|Publisher's page (for instructors' request of an evaluation copy)]] ''' cdierbach@towson.edu ''' (for questions, and example textbook materials) ---- '''Building Skills in Object-Oriented Design''' Steven F. Lott How do you move from OO programming to OO design? Do a lot of design focused on building a sophisticated application program. This 269-page book has 43 chapters that will help you build OO design skills through the creation of a moderately complex family of application programs. This is a step-by-step guide to OO design and implementation using either the Java or Python programming languages. http://homepage.mac.com/s_lott/books/oodesign.html ---- '''Problem Solving with Algorithms and Data Structures''' . Brad Miller and David Ranum ISBN:1590280539, Franklin Beedle & Associates, December 2005 This is a textbook for a CS2 Data Structures Course. [[http://knuth.luther.edu/~bmiller/python.html|Home Page]] ---- |
Network Science with Python and NetworkX Quick Start Guide
Edward Platt
ISBN 13: 9781789955316 Packt 190 Pages (25 Apr 2019)
Book Overview:
Manipulate and analyze network data with the power of Python and NetworkX
NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use.
With this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems.
Data Science Projects with Python
Steve Klosterman
ISBN 13: 9781838551025 Packt 374 Pages (29 Apr 2019)
Book Overview:
A case study approach to successful data science projects using Python, pandas, and scikit-learn
Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The book will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive.
With this book, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data.
Applied Supervised Learning with Python
Benjamin Johnston and Ishita Mathur
ISBN 13: 9781789954920 Packt 404 Pages (26 Apr 2019)
Book Overview:
Explore the exciting world of machine learning with the fastest growing technology in the world
Machine learning—the ability of a machine to give right answers based on input data—has revolutionized the way we do business. Applied Supervised Learning with Python provides a rich understanding of how you can apply machine learning techniques in your data science projects using Python. You'll explore Jupyter Notebooks, the technology used commonly in academic and commercial circles with in-line code running support.
With this book, you'll be equipped to not only work with machine learning algorithms, but also be able to create some of your own!
Hands-On Unsupervised Learning with Python
Giuseppe Bonaccorso
ISBN 13: 9781789348279 Packt 386 Pages (28 Feb 2019)
Book Overview:
Discover the skill-sets required to implement various approaches to Machine Learning with Python
Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python.
With this book, you will have learned the art of unsupervised learning for different real-world challenges.
Mastering Python for Finance - Second Edition
James Ma Weiming
ISBN 13: 9781789346466 Packt 426 Pages(29 Apr 2019)
Book Overview:
Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications
The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples.
With this book, you will also be able to apply Python to different paradigms in the financial industry and perform efficient data analysis.
Python Parallel Programming Cookbook - Second Edition
Giancarlo Zaccone
ISBN 13: 9781789533736 Packt 370 Pages (6 Sep 2019)
Book:
Implement effective programming techniques in Python to build scalable software that saves time and memory
This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications.
With this book, you will be confident in building concurrent and high-performing applications in Python.
Hands-On Neuroevolution with Python
Iaroslav Omelianenko
ISBN 13 :9781838824914 Packt 368 pages (December 24, 2019)
Book Overview:
Neuroevolution is a form of artificial intelligence learning that uses evolutionary algorithms to simplify the process of solving complex tasks in domains such as games, robotics, and the simulation of natural processes. This book will give you comprehensive insights into essential neuroevolution concepts and equip you with the skills you need to apply neuroevolution-based algorithms to solve practical, real-world problems.
You'll start with learning the key neuroevolution concepts and methods by writing code with Python. You'll also get hands-on experience with popular Python libraries and cover examples of classical reinforcement learning, path planning for autonomous agents, and developing agents to autonomously play Atari games. Next, you'll learn to solve common and not-so-common challenges in natural computing using neuroevolution-based algorithms. Later, you'll understand how to apply neuroevolution strategies to existing neural network designs to improve training and inference performance. Finally, you'll gain clear insights into the topology of neural networks and how neuroevolution allows you to develop complex networks, starting with simple ones.
By the end of this book, you will not only have explored existing neuroevolution-based algorithms, but also have the skills you need to apply them in your research and work assignments.
Mastering pandas - Second Edition
Ashish Kumar
ISBN 13: 9781789343236 Packt Course Length: 20 hours 13 minutes (25 Oct 2019)
Video Overview:
Perform advanced data manipulation tasks using pandas and become an expert data analyst.
pandas is a popular Python library used by data scientists and analysts worldwide to manipulate and analyze their data. This book presents useful data manipulation techniques in pandas to perform complex data analysis in various domains.
With this book, you will learn how to perform efficient data analysis using pandas on complex data, and become an expert data analyst or data scientist in the process.
Python API Development Fundamentals
Jack Huang, Ray Chung, Et al
ISBN 13 :9781838983994 Packt 372 Pages (22 Nov 2019)
Book Overview:
Learn all that’s needed to build a fully functional web application from scratch.
Python is a flexible language that can be used for much more than just script development. By knowing the Python RESTful APIs work, you can build a powerful backend for web applications and mobile applications using Python.
You'll take your first steps by building a simple API and learning how the frontend web interface can communicate with the backend. You'll also learn how to serialize and deserialize objects using the marshmallow library. Then, you'll learn how to authenticate and authorize users using Flask-JWT. You'll also learn how to enhance your APIs by adding useful features, such as email, image upload, searching, and pagination. You'll wrap up the whole book by deploying your APIs to the cloud.
By the end of this book, you'll have the confidence and skill to leverage the power of RESTful APIs and Python to build efficient web applications.
Full-Stack React, Python, and GraphQL [Video]
Reed Barger
ISBN 13: 9781839215698 Packt Course Length: 6 hours 35 minutes (24 Oct 2019)
Video Overview:
Develop impressive, rich full-stack apps with the latest and greatest features of Python, React, and GraphQL
This course is for developers keen to build complete, full-stack applications with cutting-edge React user interfaces, powered by a robust Python backend and using GraphQL on the server and client. This course was designed for developers keen to get ahead of the curve in the latest web technologies, and focuses on how to use GraphQL from front to back, the most current techniques and tools in React (including React Hooks, Apollo Boost, and Material UI), and how to combine it all with Python, Django, and Graphene for an amazing stack.
You'll be building a full-stack app from scratch with a GraphQL API made with Python (Django and Graphene); a React client app with React Hooks and Apollo Boost; state management React Context (with useContext) and Apollo Client State, media file uploads with Cloudinary; and tons more.
This app will be a social music-sharing app called ReactTracks where users can upload and share any music they like, interact with various tracks by liking them and adding them to their profile, searching for tracks, adding information about their music, and editing/deleting their tracks.
Learn Python and Ethical Hacking from Scratch [Video]
Zaid Sabih
ISBN 13:9781839214561 Packt course Length: 23 hours 29 minutes (11 Oct 2019)
Video Overview:
Start from scratch and learn both topics simultaneously by writing 20+ hacking programs
This course is highly practical but doesn't neglect the theory, so we start by covering some basics for ethical hacking and Python programming, installing the required software, and then starting to program straightaway.
So, by the end of the course, you'll have the programming skills to write any program even if it has nothing to do with hacking, but you'll learn to program by programming hacking tools!
All the code files are placed at https://github.com/PacktPublishing/Learn-Python-and-Ethical-Hacking-From-Scratch
Reinforcement Learning Algorithms with Python
Andrea Lonza
ISBN 13:9781789131116 Packt 366 Pages (18 Oct 2019)
Book Overview:
Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries
Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behaviour based on changing requirements. This book will help you master RL algorithms and understand their implementation as you build self-learning agents.
By the end of the book, you'll have worked with key RL algorithms to overcome challenges in real-world applications and be part of the RL research community.
Python A-Z - Learn Python Programming By Building 5 Projects [Video]
Shubham Sarda
ISBN 13: 9781839212956 Packt Course Length: 12 hours 21 minutes 11 Oct 2019 (MONTH YEAR)
Video Overview:
Python programming masterclass for beginners – learn all about Python 3 with object-oriented concepts, five projects and more!
Welcome to “Python Programming A-Z – Learn Python Programming by Building Five Projects,” a course that takes you through your Python journey from beginner to advanced step by step. This course touches on every important concept of the latest version of Python, Python 3. Throughout the course, we will explore the most essential Python features:
After completing this course, you will be ready to work as an intern, fresher, or freelancer, and you will also be able to implement everything yourself! Most importantly, you will be ready to use the huge scope offered by Python programming.
All the codes and supporting files for this course are available at -https://github.com/PacktPublishing/Python-A-Z---Learn-Python-Programming-By-Building-5-Projects
Python Parallel Programming Cookbook - Second Edition
Giancarlo Zaccone
ISBN 13: 9781789533736 Packt 370 pages Pages: 11 hours 6 minutes (6 Sep 2019)
Book Overview:
Implement effective programming techniques in Python to build scalable software that saves time and memory
Nowadays, it has become extremely important for programmers to understand the link between the software and the parallel nature of their hardware so that their programs run efficiently on computer architectures. Applications based on parallel programming are fast, robust, and easily scalable.
This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications.
With this book, you will be confident in building concurrent and high-performing applications in Python.
Python GUI Programming Cookbook - Third Edition
Burkhard Meier
ISBN 13: 9781838827540 Packt 486 Pages (11 Oct 2019)
Book Overview:
Over 90 recipes to help you develop widgets, forms, layouts, charts, and much more using the latest features of Python 3
Python is a multi-domain, interpreted programming language that is easy to learn and implement. With its wide support for frameworks to develop GUIs, you can build interactive and beautiful GUI-based applications easily using Python. This third edition of Python GUI Programming Cookbook follows a task-based approach to help you create effective GUIs with the smallest amount of code. Every recipe in this book builds upon the last to create an entire, real-life GUI application. These recipes also help you solve problems that you might encounter while developing GUIs. This book mainly focuses on using Python’s built-in tkinter GUI framework. You'll learn how to create GUIs in Python using simple programming styles and object-oriented programming (OOP). As you add more widgets and expand your GUI, you will learn how to connect to networks, databases, and graphical libraries that greatly enhance the functionality of your GUI. You’ll also learn how to use threading to ensure that your GUI doesn't become unresponsive. Toward the end, you’ll learn about the versatile PyQt GUI framework, which comes along with its own visual editor that allows you to design GUIs using drag and drop features. By the end of the book, you’ll be an expert in designing Python GUIs and be able to develop a variety of GUI applications with ease.
Python GUI Programming - A Complete Reference Guide
Alan D. Moore and B.M. Harwani
ISBN 13: 9781838988470 Packt 746 Pages (24 Jun 2019)
Book Overview:
Explore Python’s GUI frameworks and create visually stunning and feature-rich applications
This Learning Path begins by introducing you to Tkinter and PyQt, before guiding you through the application development process. As you expand your GUI by adding more widgets, you'll work with networks, databases, and graphical libraries that enhance its functionality. You'll also learn how to connect to external databases and network resources, test your code, and maximize performance using asynchronous programming. In later chapters, you'll understand how to use the cross-platform features of Tkinter and Qt5 to maintain compatibility across platforms. You’ll be able to mimic the platform-native look and feel, and build executables for deployment across popular computing platforms.
With this book you'll have the skills and confidence to design and build high-end GUI applications that can solve real-world problems.
Peter Fisher
ISBN 13: 9781788831079 Course Length: 2 hours 8 minutes (3 Jul 2019)
Video Overview:
Discover simple practices for writing clean and efficient Python code
Even bad code can function. But if code isn't clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn't have to be that way.
With this course we will apply what we’ve learned in the previous videos to rewriting and reorganizing real-world Python programs into clean and beautiful code that can be more easily understood, debugged, and extended.
Python GUI Programming - A Complete Reference Guide
Alan D. Moore and B.M. Harwani
ISBN 13: 9781838988470 Packt 746 Pages Course Length: 22 hours 22 minutes (24 Jun 2019)
Book:
Explore Python’s GUI frameworks and create visually stunning and feature-rich applications
A responsive graphical user interface (GUI) helps you interact with your application, improves user experience, and enhances the efficiency of your applications. With Python, you’ll have access to elaborate GUI frameworks that you can use to build interactive GUIs that stand apart from the rest.
With this book you'll have the skills and confidence to design and build high-end GUI applications that can solve real-world problems.
Hands-On Qt for Python Developers
Volodymyr Kirichinets
ISBN 13: 9781789612790 Packt 770 Pages (29 May 2019)
Book Overview:
Boost UI development with ready-made widgets, controls, charts, and data visualization and create stunning 2D and 3D graphics with PyQt and PySide2.
Qt is one of the most widely used and flexible frameworks for GUI application development, allowing you to write your application once and then deploy it to multiple operating systems. This book combines the best of Python and Qt to help you develop GUI applications with Python bindings, such as PyQt and PySide, that will supercharge your Python applications.
With this book, you will be able to create modern, responsive, cross-platform desktop applications with the power of Qt, Python, and QML.
Deep Learning and Neural Networks using Python - Keras: The Complete Beginners Guide
Abilash Nelson
ISBN 13: 9781838986476 Packt Course Length: 11 hours 7 minutes (28 May 2019)
Video Overview:
Deep learning and data science using a Python and Keras library - The complete guide from a beginner to professional
The world has been obsessed with the terms "machine learning" and "deep learning" recently. We use these technologies every day, with or without our knowledge. Ranging from Google suggestions to translations, ads, movie recommendations, friend suggestions, sales and customer experiences. There are tons of other applications too so there’s no wonder that deep learning and machine learning specialists, along with data science practitioners, are the most sought-after talent in the current technology world. But the problem is that, when you think about learning these technologies, there is a common misconception that it’s a prerequisite to study lots of maths, statistics, and complex algorithms. It’s almost like someone making you believe that you must learn the working of an internal combustion engine before you learn how to drive a car
This course is organized and an overview of the list of topics included. Overall, this is a basic to an advanced crash course in deep learning neural networks and convolutional neural networks using Keras and Python.
Using MySQL Databases With Python
John Elder
ISBN 13: 9781838984670 Packt Course Length: 2 hours 2 minutes (28 May 2019)
Video Overview:
Learn the MySql Database with Python the fast and easy way!
These days, everything uses a database, and MySQL is one of the most popular databases out there. FREE and Open Source, Mysql is a great database for just about all of your needs. Likewise, Python is one of the most popular and powerful programming languages today. Pairing the two together is a powerful combination!
With this course, you'll learn the basics of using MySQL with Python. You'll learn how to create databases and tables, add data, sort data, create reports, pull specific data, and more.
Hands-On Qt for Python Developers
Volodymyr Kirichinets
ISBN 13: 9781789612790 Packt 770 Pages (29 May 2019)
Book:
Boost UI development with ready-made widgets, controls, charts, and data visualization and create stunning 2D and 3D graphics with PyQt and PySide2.
The book begins with an overview of Qt and QML. You’ll start by working with PyQt GUI elements to style your applications. Then, you will learn how to use QWidget, frames, labels, and text fields, and work with graphics. This will be followed by taking you through how elements in the application communicate with each other by understanding signals, slots, and event handlers. This book will help you to gain a better understanding of the Qt framework and the tools to resolve issues when testing, linking, debugging, and multithreading your Python GUI applications. Finally, the book will help you get to grips with embedded and mobile development using PyQt and PySide.
With this book, you will be able to create modern, responsive, cross-platform desktop applications with the power of Qt, Python, and QML.
Hands-On GPU Computing with Python
Avimanyu Bandyopadhyay
ISBN 13: 9781789341072 Packt 452 Pages (13 May 2019)
Book:
Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate
This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you’ll look at using integrations such as PyCUDA, PyOpenCL, CuPy, and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance.
With this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly.
Mastering GUI Programming with Python
Alan D. Moore
ISBN : 9781789612905 Packt Pages : 542 pages (23 May 2019)
Book Overview:
An advanced guide to creating powerful high-performance GUIs for modern, media-rich applications in various domains such as business and game development
You will get started with an introduction to PyQt5, before going on to develop stunning GUIs with modern features. You will then learn how to build forms using QWidgets and learn about important aspects of GUI development such as layouts, size policies, and event-driven programming. Moving ahead, you’ll discover PyQt5’s most powerful features through chapters on audio-visual programming with QtMultimedia, database-driven software with QtSQL, and web browsing with QtWebEngine. Next, in-depth coverage of multithreading and asynchronous programming will help you run tasks asynchronously and build high-concurrency processes with ease. In later chapters, you’ll gain insights into QOpenGLWidget, along with mastering techniques for creating 2D graphics with QPainter. You’ll also explore PyQt on a Raspberry Pi and interface it with remote systems using QtNetwork. Finally, you will learn how to distribute your applications using setuptools and PyInstaller.
By the end of this book, you will have the skills you need to develop robust GUI applications using PyQt.
Marwan Alsabbagh
ISBN :9781838649951 Packt Pages : 452 (20 May 2019)
Book Overview: Build practical solutions to control LEDs, make music and read sensor data using popular microcontrollers such as Adafruit Circuit Playground, ESP8266, and the BBC Micro Bit
The MicroPython book covers recipes that will help you experiment with the programming environment and hardware programmed in MicroPython. You'll find tips and techniques for building a variety of objects and prototypes that can sense and respond to touch, sound, position, heat, and light. This book will take you through the uses of MicroPython with a variety of popular input devices and sensors. You'll learn techniques to handle time delays and sensor readings, and apply advanced coding techniques to create complex projects. As you advance, you'll deal with Internet of Things (IoT) devices and integration with other online web services. Furthermore, you'll also use MicroPython to make music with bananas and create portable multiplayer video games that incorporate sound and light animations into the gameplay.
By the end of the book, you'll have mastered the tips and tricks to troubleshoot your development problems and push your MicroPython project to the next level!
Real World Projects in Python 3.x
- Matthew Macarty
ISBN 13: 9781789953374 Packt Course Length: 2 hours 23 minutes (29 Apr 2019)
Video Overview:
Step by Step practical guide for building real-world projects using Python 3
This course covers the essential concepts in Python 3 showing how to implement them in various applications. You’ll learn about Python 3.x new features and develop the skills required for building robust, easily scalable, and maintainable code in Python.Throughout this course, you will be building multiple applications ranging from simpler ones to more complex ones. Learning by doing has its advantages as you will immediately see the concepts explained in action. You will learn how to build scalable, resilient, and effective applications as real-world projects in Python 3.x that suit your software requirements and also furthers your understanding of the Python programming language. By the end of the course, you will build upon your basic programming skills taking your programming skills to another level and conveniently build projects with Python 3.x as per your need.
Applied Deep Learning with PyTorch
Hyatt Saleh
ISBN 13: 9781789804591 Packt 254 Pages (26 Apr 2019)
Book Overview:
Implement techniques such as image classification and natural language processing (NLP) by understanding the different neural network architectures
Machine learning is rapidly becoming the most preferred way of solving data problems, thanks to the huge variety of mathematical algorithms that find patterns, which are otherwise invisible to us.
With this book, you’ll be able to apply the skills and confidence you've gathered along your learning process to use PyTorch for building deep learning solutions that can solve your business data problems.
Python Data Mining Quick Start Guide
Nathan Greeneltch
ISBN 13: 9781789800265 Packt 188 Pages (24 Apr 2019)
Book OR Video Overview:
Explore the different data mining techniques using the libraries and packages offered by Python
Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining.
With this book, you will be able to build an efficient data mining pipeline using Python without any hassle.
--- Troubleshooting Python Deep Learning [Video]
Jakub Konczyk
ISBN 13: 9781788998192 Packt Course Length: 3 hours 2 minutes ( 29 April 2019)
Video Overview:
After carefully analyzing the most popular errors or problems that arise while working on Deep Learning models, we have identified the most usable models used for classification in this course and provided practical yet unique solutions to each problem that are easy to understand and implement. You can either follow the entire course or directly jump into the section that covers a specific problem you’re facing. Some of the common yet important issues we cover include errors while building and training Deep Learning with neural networks, especially without a specific framework.
By the end of the course, you will be well-versed to tackle and troubleshoot any errors with your Deep learning models.
Hands-On Deep Learning Architectures with Python
Yuxi (Hayden) Liu, Saransh Mehta
ISBN 13: 9781788998086 Packt 316 Pages (April 2019)
Book Overview:
Concepts, tools, and techniques to explore deep learning architectures and methodologies
Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and implement deep learning architectures to resolve various deep learning research problems.
With this book you will be able to construct deep models using popular frameworks and datasets with the required design patterns for each architecture. You will be ready to explore the potential of deep architectures in today's world.
OpenCV Computer Vision Examples with Python: A Complete Guide for Dummies [Video]
Abhilash Nelson
ISBN 13: 9781838820817 Packt Course Length: 08 hours 50 minutes (March 2019)
Video Overview:
Computer Vision is an AI based, that is, Artificial Intelligence-based technology that allows computers to understand and label images. So, learning and mastering this fantastic world of Computer Vision-based technology is surely up-market. It will make you proficient in competing with the swiftly changing Image Processing technology arena. And this course is designed in such a way that even the very beginner to programming can master the Computer Vision-based technology.
So, overall this is a complete package in which you can learn Computer Vision-based Technology, Deep Learning-based Face Detection, then Face Recognition and Optical Character Recognition.
Artificial Intelligence in 3 Hours [Video]
Luka Anicin
ISBN 13: 9781838646196 Packt Course Length: 03 hours 05 minutes (March 2019)
Video Overview:
Get up and running with AI in less than 3 hours
What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common? They are all complex real-world problems being solved with applications of intelligence (AI). This course provides you with a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.
A comprehensive course that takes you through AI in 3 hours. It is packed with step by step instructions and working examples.
Hands-On Artificial Intelligence with Keras and Python [Video]
Sandipan Das
ISBN 13: 9781838557829 Packt Course Length: 2 hours 31 minutes (March 2019)
Video Overview:
Use Keras to solve advanced industry relevant projects
AI will help you solve key challenges in the future in several domains. It is an exciting time to be doing AI with world making its shift towards Industry 2.0 with automation in focus.
This course will help you learn by doing an industry relevant problem in image processing domain, develop and understand automation and AI techniques. You will learn how to harness the power of algorithms by creating apps which intelligently interact with the world around you, addressing common challenges faced in AI ecosystem.
Hands-On Python 3.x GUI Programming [Video]
Burkhard Meier
ISBN 13: 9781789957242 Course Length: 2 hours 56 minutes (March 2019)
Video Overview:
Create complete fluid, interactive and powerful applications with Tkinter & PyQt5
One cannot ignore the benefits of a well-designed architecture and graphical user interface for applications. If you're interested in designing and building graphical user interfaces that are functional, appealing, and user-friendly using one of the most powerful languages, Python 3. This course is for you. It is meant for intermediate level programmers who want to enhance their skills by developing GUIs written in Python.
By the end of this course, you will have successfully mastered high-end GUI application such as Card Game and Paint App and will be capable of building many more powerful, cross-platform, and scalable applications.
Full-Stack Web Development with Flask [Video]
Christian Hur
ISBN 13: 9781789957464 Course Length: 5 hours 10 minutes (March 2019)
Video Overview:
Learn to create and deploy simple yet powerful websites using the Flask Framework
In this course, we will cover everything you need to know to build a dynamic web application using the Python and Flask frameworks for seamless full-stack web development. You'll dive into the Flask environment and get to know its directory structure, template, and routing systems. Then you'll learn to connect to databases such as Flask-SQLAlchemy and Flask-MongoEngine to help store and track data.
The course will develop your experience in Flask and when you've completed it you will be able to build your own complex web applications.
PyTorch Deep Learning in 7 Days [Video]
Will Ballard
ISBN 13: 9781789135367 Packt Course Length: 2 hours 9 minutes (March 2019)
Video Overview:
Seven short lessons and a daily exercise, carefully chosen to get you started with PyTorch Deep Learning faster than other courses
PyTorch is Facebook’s latest Python-based framework for Deep Learning. It has the ability to create dynamic Neural Networks on CPUs and GPUs, both with significantly less code compared to other competing frameworks. PyTorch has a unique interface that makes it as easy to learn as NumPy.
This 7-day course is for those who are in a hurry to get started with PyTorch. You will be introduced to the most commonly used Deep Learning models, techniques, and algorithms through PyTorch code. This course is an attempt to break the myth that Deep Learning is complicated and show you that with the right choice of tools combined with a simple and intuitive explanation of core concepts, Deep Learning is as accessible as any other application development technologies out there. It’s a journey from diving deep into the fundamentals to getting acquainted with the advanced concepts such as Transfer Learning, Natural Language Processing and implementation of Generative Adversarial Networks.
Hands-On Big Data Analytics with PySpark
Rudy Lai, Bartłomiej Potaczek
ISBN 13: 9781838644130 Packt 182 Pages (March 2019)
Book Overview:
Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobs
Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs.
You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark.
Learning Python Networking - Second Edition
José Manuel Ortega, Dr. M. O. Faruque Sarker, Sam Washington
ISBN 13: 9781789958096 Packt 490 Pages (March 2019)
Book Overview:
Take your networking skills to the next level by learning network programming concepts and algorithms using Python
Network programming has always been a demanding task. With full-featured and well-documented libraries all the way up the stack, Python makes network programming the enjoyable experience it should be.
Starting with a walk through of today's major networking protocols, through this book, you'll learn how to employ Python for network programming, how to request and retrieve web resources, and how to extract data in major formats over the web. You will utilize Python for emailing using different protocols, and you'll interact with remote systems and IP and DNS networking. You will cover the connection of networking devices and configuration using Python 3.7, along with cloud-based network management tasks using Python.
Data Science for Marketing Analytics
Tommy Blanchard, Debasish Behera, Pranshu Bhatnagar
ISBN 13: 9781789959413 Packt 420 Pages (March 2019)
Book Overview:
Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results
Data Science for Marketing Analytics takes a hands-on approach to the practical aspects of using Python data analytics libraries to ease marketing analytics efforts. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.
The book is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.
Python Machine Learning Cookbook - Second Edition
Giuseppe Ciaburro, Prateek Joshi
ISBN 13: 9781789808452 Packt 642 Pages (March 2019)
Book Overview:
Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch
This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks.
With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach.
Hands-On Natural Language Processing with Pytorch {Video}
Jibin Mathew
ISBN 13: 9781789133974 Packt Course Length: 2 hours 24 minutes (January 2019)
Video Overview:
Use modern NLP tools & techniques with Deep Learning & PyTorch to build intelligent language applications
The main goal of this course is to train you to perform complex NLP tasks (and build intelligent language applications) using Deep Learning with PyTorch.
You will build two complete real-world NLP applications throughout the course. The first application is a Sentiment Analyzer that analyzes data to determine whether a review is positive or negative towards a particular movie. You will then create an advanced Neural Translation Machine that is a speech translation engine, using Sequence to Sequence models with the speed and flexibility of PyTorch to translate given text into different languages.
Artificial Intelligence and Machine Learning Fundamentals
Zsolt Nagy
ISBN 13: 9781789801651 Packt 330 Pages (December 2018)
Book Overview:
Create AI applications in Python and lay the foundations for your career in data science
As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law.
By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!
David Taieb
ISBN 13: 9781789950069 Packt 490 Pages (December 2018)
Book Overview:
Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis.
Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing.
The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.
Computer Vision Projects with OpenCV and Python 3
Matthew Rever
ISBN 13: 9781789954555 Packt 182 Pages (December 2018)
Book Overview:
Gain a working knowledge of advanced machine learning and explore Python’s powerful tools for extracting data from images and videos
With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow.
By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries.
Introduction to Bayesian Analysis in Python (Video)
Sunil Gupta
ISBN 13: 9781788997010 Packt Course Length: 1 hour 10 minutes (December 2018)
Video Overview:
This course focuses on the application of relevant Bayesian techniques
The course introduces the framework of Bayesian Analysis. Complex mathematical theory will be sidestepped in favor of a more pragmatic approach, featuring computational methods implemented in the Python library PyMC3. We present several instances of analysis scenarios.
All the codes of the course are uploaded on the Github repository: https://github.com/PacktPublishing/-Introduction-to-Bayesian-Analysis-in-Python
Deep Learning for Python Developers {Video}
Will Ballard
ISBN 13: 9781788993883 Packt Course Length: 2 hours 11 minutes (December 2018)
Video Overview:
Use your Python skills to build powerful Deep Learning applications
This course is for Python developers who haven't worked with machine learning or data science, and want to build intelligent systems right away—without taking a math degree! You will learn about recurrent neural networks, Backprop, SGD, and more. You will work on code examples that are used in a developer's life on a daily basis; you'll not only master the theory, you'll also see how to applied it in the industry as a whole. You will practice all these ideas in MxNet, TensorFlow, Keras, and Gluon. Last but not the least, build Convolutional Neural Networks and apply them to image data.
Deep Learning is currently enabling numerous exciting applications in speech recognition, music synthesis, machine translation, natural language understanding, and many others. AI is transforming multiple industries. After finishing this course, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI.
Hands-On Enterprise Application Development with Python
Saurabh Badhwar
ISBN 13: 9781789532364 Packt 374 pages (December 2018)
Book Overview:
Dynamically typed languages like Python are continuously improving. With the addition of exciting new features and a wide selection of modern libraries and frameworks, Python has emerged as an ideal language for developing enterprise applications. Hands-On Enterprise Application Development with Python will show you how to build effective applications that are stable, secure, and easily scalable.
The book is a detailed guide to building an end-to-end enterprise-grade application in Python. You will learn how to effectively implement Python features and design patterns that will positively impact your application lifecycle. The book also covers advanced concurrency techniques that will help you build a RESTful application with an optimized frontend. Given that security and stability are the foundation for an enterprise application, you’ll be trained on effective testing, performance analysis, and security practices, and understand how to embed them in your codebase during the initial phase. You’ll also be guided in how to move on from a monolithic architecture to one that is service oriented, leveraging microservices and serverless deployment techniques.
By the end of the book, you will have become proficient at building efficient enterprise applications in Python.
Bayesian Analysis with Python - Second Edition
Osvaldo Martin
ISBN 13: 9781789341652 Packt 356 Pages (December 2018)
Book Overview:
Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ
The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models.
The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others.
Hands-On Predictive Analytics with Python
Alvaro Fuentes
ISBN 13: 9781789138719 Packt 330 Pages (December 2018)
Book Overview:
Step-by-step guide to build high performing predictive applications
Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages.
The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model.
Learning Python Artificial Intelligence by Example (Video)
Mark Strefford
ISBN 13: 9781788839532 Packt Course Length: 1 hour 58 minutes (November 2018)
Video Overview:
Build interactive chatbots, facial recognition, headline writers, and more. No AI experience required!
Built for rookie AI enthusiasts across four realistic projects, this course covers modern techniques that make up the world of Artificial Intelligence. Dive into your first natural language processing project, build a facial recognition system, and build your very own self driving steering code. You will explore the use of neural networks and deep learning, and how you can train and test sets for feature extraction. You'll be introduced to the Keras deep learning library, which you will use to predict taxi journey times, and to the use of natural language processing to find the most relevant articles in Wikipedia.
By the end of this video course, you will be confident enough to build your own AI projects with Python, and ready to take on more advanced content as you move on.
Consuming Python APIs with React (Video)
Wayne Merry
ISBN 13: 9781788396073 Packt Course Length: 2 hours 21 minutes (November 2018 )
Video Overview:
Bring your Python full stack web development experience full circle by integrating your Django backend with a React frontend
You will start by quickly setting up your JavaScript tools and Node.js, as well as React.js for a Bookmarking Application project. After that, you will put together your basic frontend code for interacting with your Django backend. You will learn to build and use React components for your application's UI, and work with your React code's data and state to determine how your application behaves. You'll also explore routing and event handling for your application. From there, you will delve into backend interaction details, such as authentication for login. You will learn to consume your Django resources and also create, update, and delete item data.
You'll also learn specific tasks such as managing your bookmarks and counting and collecting likes and comments on your bookmarks. By the end of this course, you will have successfully integrated your Python web application's backend with a React.js frontend.
Bioinformatics with Python Cookbook - Second Edition
Tiago Antao
ISBN 13: 9781789344691 Packt 360 Pages (November 2018)
Book Overview:
Discover modern, next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data
Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data.
This book covers next-generation sequencing, genomics, metagenomics, population genetics, phylogenetics, and proteomics. You'll learn modern programming techniques to analyze large amounts of biological data. With the help of real-world examples, you'll convert, analyze, and visualize datasets using various Python tools and libraries.
Hands-On Image Processing with Python
Sandipan Dey
ISBN 13: 9781789343731 Packt 492 Pages (November 2018)
Book Overview:
Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks.
Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python.
The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing.
Natural Language Processing with Python Quick Start Guide
Nirant Kasliwal
ISBN 13: 9781789130386 Packt 182 Pages (November 2018)
Book Overview:
Going from a Python developer to an effective Natural Language Processing Engineer
NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.
The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a workflow for building NLP applications.
Recurrent Neural Networks with Python Quick Start Guide
Simeon Kostadinov
ISBN 13: 9781789132335 Packt 122 Pages November 2018)
Book Overview:
Learn how to develop intelligent applications with sequential learning and apply modern methods for language modeling with neural network architectures for deep learning with Python's most popular TensorFlow framework.
Developers struggle to find an easy-to-follow learning resource for implementing Recurrent Neural Network (RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve results. This book will teach you the fundamentals of RNNs, with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling.
Your journey starts with the simplest RNN model, where you can grasp the fundamentals. The book then builds on this by proposing more advanced and complex algorithms. We use them to explain how a typical state-of-the-art RNN model works. From generating text to building a language translator, we show how some of today's most powerful AI applications work under the hood.
After reading the book, you will be confident with the fundamentals of RNNs, and be ready to pursue further study, along with developing skills in this exciting field.
Hands-On GPU Programming with Python and CUDA
Dr. Brian Tuomanen
ISBN 13: 9781788993913 Packt 310 Pages November 2018)
Book Overview:
Build real-world applications with Python 2.7, CUDA 9, and CUDA 10
Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler to identify bottlenecks in your Python code, and set up an appropriate GPU programming environment. You’ll then see how to “query” the GPU’s features and copy arrays of data to and from the GPU’s own memory.
As you make your way through the book, you’ll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You’ll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you’ll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS.
With a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You’ll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you’ll see some topics and applications related to GPU programming that you may wish to pursue, including AI, graphics, and blockchain.
By the end of this book, you will be able to apply GPU programming to problems related to data science and high-performance computing.
Colibri Digital
ISBN 13: 9781789618464 Packt Course Length: 2 hours 31 minutes (November 2018)
Video Overview:
Dive right into the world of Computer Vision and AI by making five awesome, real-life applications with this hands-on course
The scope of computer vision has been booming in the past few years and it has become a highly sought-after skill. There are tons of real-life problems just waiting to be solved with computer vision. If you want to get your hands dirty with this technology and use it to craft your own, unique solutions, then look no further because this course is made for you!
The course is designed so you’ll learn as you develop interesting apps. First you’ll learn to set up your environment, before building five exciting applications. We’ll introduce you to all necessary concepts and slowly transition into the field of Artificial Intelligence (AI) and deep learning such as classification and object detection.
Mastering Concurrency in Python
Quan Nguyen
ISBN 13: 9781789343052 Packt 446 Pages (November 2018)
Book Overview:
Immerse yourself in the world of Python concurrency and tackle the most complex concurrent programming problems
Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently, but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming.
Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples.
Hands-On Reactive Programming with Python
Syeda Seemab
ISBN 13: 9781789138795 Packt Course Length: 2 hours 34 minutes (November 2018)
Video Overview:
Build reactive applications with Python. Make your applications concurrent and asynchronous with RxPY
This practical guide will take you steadily through an exploration of Reactive Programming. In this course, you will learn about Reactive Programming in Python using RxPY and simplify the way you write code and create robust enterprise applications. The course covers the major libraries on Python reactive extensions (RxPY) and explains in detail the role of asynchronous programming and event-based programming in building reactive extensions. You will look deep into its provided classes, methods, and operators, to help you to build a reactive application.
By the end of the course, you will be equipped to solve real-world problems and have a clear understanding of when and how you should use the different approaches demonstrated in RxPY.
Application Development with Python and Flask
Achim Takunda Munene
ISBN 13: 9781788991575 Course Length: 6 hours 7 minutes (November 2018)
Video Overview:
Dive into the world of Flask Framework in Python to build an array of simple yet powerful web applications
This course will take you through Flask Microframework; it covers all its components and elements and how to integrate it with useful third-party libraries. You will download all you need to get started with Flask development and then delve straight into the frontend and backend development stack. The course will then show you the general flow in developing a Flask application, including some extensions used by developing a simple application. You will then develop multiple applications such as note-taking, social medias, and file sharing applications.
By the end of the course, you will be able to build your own web applications using Flask in Python.
Hands-On Software Engineering with Python
Brian Allbee
ISBN 13: 9781788622011 Packt 736 Pages (October, 2018)
Book Overview:
Explore various verticals in software engineering through high-end systems using Python
Software Engineering is about more than just writing code—it includes a host of soft skills that apply to almost any development effort, no matter what the language, development methodology, or scope of the project. Being a senior developer all but requires awareness of how those skills, along with their expected technical counterparts, mesh together through a project's life cycle.
This book walks you through that discovery by going over the entire life cycle of a multi-tier system and its related software projects. You'll see what happens before any development takes place, and what impact the decisions and designs made at each step have on the development process. The development of the entire project, over the course of several iterations based on real-world Agile iterations, will be executed, sometimes starting from nothing, in one of the fastest growing languages in the world—Python. Application of practices in Python will be laid out, along with a number of Python-specific capabilities that are often overlooked. Finally, the book will implement a high-performance computing solution, from first principles through complete foundation.
Hands-On Data Structures and Algorithms with Python - Second Edition
Dr. Basant Agarwal
ISBN 13: 9781788995573 Packt 398 Pages (October, 2018)
Book Overview:
Learn to implement complex data structures and algorithms using Python
This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.
By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.
The Complete Machine Learning Course with Python (Video)
Anthony NG, Rob Perciva
ISBN 13: 9781789953725 Packt Course Length: 18 hours 22 minutes (October, 2018)
Video Overview:
Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!
You will train machine learning algorithms to classify flowers, predict house price, identify handwritings or digits, identify staff that is most likely to leave prematurely, detect cancer cells and much more!
By the end of this course, you will have a Portfolio of 12 Machine Learning projects that will help you land your dream job or enable you to solve real-life problems in your business, job or personal life with Machine Learning algorithms.
Master Computer Vision OpenCV3 in Python and Machine Learning (Video)
Rajeev Ratan
ISBN 13: 9781789616521 Packt Course Length: 6 hours 14 minutes (October 2018)
Video Overview:
Learn Computer Vision concepts by building 12 projects, including handwriting recognition, face filters, and car and people detection!
Computer vision applications and technology are exploding right now, with several apps and industries making amazing use of the technology—ranging from up-and-coming apps such as MSQRD, and PRISMA to billion-dollar apps such as Pokémon GO and Snapchat! Even Facebook, Google, Microsoft, Apple, Amazon, and Tesla are all heavily utilizing computer vision for face and object recognition, image searching, and especially in self-driving cars! As a result, the demand for computer vision expertise is growing exponentially! However, learning computer vision is hard! Existing online tutorials, textbooks, and free MOOCs are often outdated, using older and incompatible libraries, or are too theoretical, making the subject difficult to understand.
This was the author's problem when learning Computer Vision and it became incredibly frustrating. Even simply running example code found online proved difficult as libraries and functions were often outdated. The author created this course to teach you all the key concepts without the heavy mathematical theory—all the while using the most up-to-date methods. At the end of the course, you will be able to build 12 awesome Computer Vision apps using OpenCV (the best supported open-source computer vision library that exists today!) in Python. Using it in Python is just fantastic as Python allows us to focus on the problem at hand without getting bogged down in complex code. If you're an academic or college student but want to learn more, the author still points you in the right direction by linking the research papers for techniques used. So if you want to get an excellent foundation in Computer Vision, look no further. This is the course for you!
Python for Finance: Investment Fundamentals and Data Analytics
ISBN 13: 9781789618976 Course Length 6 hours 59 minutes (October 2018)
Video Overview:
This course will take you on a journey where you'll learn how to code in Python. You will learn how to use Python in a real working environment and explore how Python can be applied in the world of Finance to solve portfolio optimization problems. The first part of the course is ideal for beginners and people who want to brush up on their Python skills. And then, once we have covered the basics, we will be ready to tackle financial calculations and portfolio optimization tasks. The Finance block of this course will teach you in-demand, real-world skills employers are looking for. This explains topics such as how to work with Python's conditional statements, functions, sequences, and loops, build investment portfolios, and more.
The code bundle for this video course is available at https://github.com/PacktPublishing/Python-for-Finance-Investment-Fundamentals-and-Data-Analytics.
Applied Data Science with Python and Jupyter
Alex Galea
ISBN 13: 9781789958171 Packt 192 Pages (MONTH YEAR)
Book Overview:
Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications.
In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques.
You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations.
Hands-On Reactive Programming with Python
Romain Picard
ISBN 13: 9781789138726 Packt Course Length: 12 hours 36 minutes (October 2018)
Video Overview:
A comprehensive guide to help you understand the principles of Reactive and asynchronous programming and its benefits
This hands-on guide gets you started with Reactive Programming (RP) in Python. You will learn abouta the principles and benefits of using RP, which can be leveraged to build powerful concurrent applications. As you progress through the chapters, you will be introduced to the paradigm of Functional and Reactive Programming (FaRP), observables and observers, and concurrency and parallelism. The book will then take you through the implementation of an audio transcoding server and introduce you to a library that helps in the writing of FaRP code. You will understand how to use third-party services and dynamically reconfigure an application.
By the end of the book, you will also have learned how to deploy and scale your applications with Docker and Traefik and explore the significant potential behind the reactive streams concept, and you'll have got to grips with a comprehensive set of best practices.
Learn Computer Vision with Python and OpenCV [Video]
Kathiravan Natarajan
ISBN 13: 9781788293846 Packt Course Length: 1 hour 20 minutes (October 2018)
Book OR Video Overview:
Detect and track objects in images and videos. Perform accurate and reliable processing tasks with Computer vision using OpenCV
This course begins with the basics of loading and working with images. You will detect colored objects in your images easily. You will also use tools to build and apply filters in your photos and track objects in a video.
By the end of the course, you will have a firm grasp of Computer Vision techniques using OpenCV libraries. This course will be your gateway to the world of data science.
ISBN 13: 9781788397414 Packt Course Length: 1 hour 46 minutes (October 2018)
Book OR Video Overview:
Build amazing and complex reactive web applications with Vue.js
This video course shows developers how to build high-performing, reactive web interfaces with Vue.js. It starts from scratch, teaching you how to build a “Hello World!” application in Vue.js and moves towards building advanced applications step by step. You'll earn the concepts that you need to know about Vue.js. You'll build an application as you go, putting the concepts we've explained into practice. Several modern tools such as Webpack, vue-cli, hot reloading, and vue devtools will be used to develop modern web applications, focusing on the view layer to provide the most performant experience for users. Also you will use the vue-cli-based Webpack template and look at how we can build on top of that starter kit.
By the end of this course, you will be able to build complex and large web applications with Vue.js and will also understand how to make single-file-based reusable components which can be used across projects.
Hands-On Reactive Programming with Python
Romain Picard
ISBN 13: 9781789138726 Packt 420 Pages (October 2018)
Book Overview:
A comprehensive guide to help you understand the principles of Reactive and asynchronous programming and its benefits
Reactive programming is central to many concurrent systems, but it’s famous for its steep learning curve, which makes most developers feel like they're hitting a wall. With this book, you will get to grips with reactive programming by steadily exploring various concepts
This hands-on guide gets you started with Reactive Programming (RP) in Python. You will learn abouta the principles and benefits of using RP, which can be leveraged to build powerful concurrent applications. As you progress through the chapters, you will be introduced to the paradigm of Functional and Reactive Programming (FaRP), observables and observers, and concurrency and parallelism. The book will then take you through the implementation of an audio transcoding server and introduce you to a library that helps in the writing of FaRP code. You will understand how to use third-party services and dynamically reconfigure an application.
By the end of the book, you will also have learned how to deploy and scale your applications with Docker and Traefik and explore the significant potential behind the reactive streams concept, and you'll have got to grips with a comprehensive set of best practices.
Mastering Flask Web Development - Second Edition
Daniel Gaspar, Jack Stouffer
ISBN 13: 9781788995405 Packt 332 Pages (October 2018)
Book Overview:
Learn to build modern, secure, highly available web MVC applications and API’s using Python`s Flask framework.
Flask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web Development will take you on a complete tour of the Flask environment and teach you how to build a production-ready application.
You'll begin by learning about the installation of Flask and basic concepts such as MVC and accessing a database using an ORM. You will learn how to structure your application so that it can scale to any size with the help of Flask Blueprints. You'll then learn how to use Jinja2 templates with a high level of expertise. You will also learn how to develop with SQL or NoSQL databases, and how to develop REST APIs and JWT authentication. Next, you'll move on to build role-based access security and authentication using LDAP, OAuth, OpenID, and database. Also learn how to create asynchronous tasks that can scale to any load using Celery and RabbitMQ or Redis. You will also be introduced to a wide range of Flask extensions to leverage technologies such as cache, localization, and debugging. You will learn how to build your own Flask extensions, how to write tests, and how to get test coverage reports. Finally, you will learn how to deploy your application on Heroku and AWS using various technologies, such as Docker, CloudFormation, and Elastic Beanstalk, and will also learn how to develop Jenkins pipelines to build, test, and deploy applications.
Machine Learning for Healthcare Analytics Projects
Eduonix Learning Solutions
ISBN 13: 9781789536591 Packt 134 Pages (October 2018)
Book Overview:
Create real-world machine learning solutions using NumPy, pandas, matplotlib, and scikit-learn
Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics.
This book will teach you how to implement key machine learning algorithms and walk you through their use cases by employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors (KNN) models. In the final chapters, you will create a deep neural network in Keras to predict the onset of diabetes in a huge dataset of patients. You will also learn how to predict heart diseases using neural networks.
Machine Learning with scikit-learn Quick Start Guide
Kevin Jolly
ISBN 13: 9781789343700 Packt 172 Pages (October 2018)
Book Overview:
Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering.
Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize, and evaluate all of the important machine learning algorithms that scikit-learn provides.
This book teaches you how to use scikit-learn for machine learning. You will start by setting up and configuring your machine learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine learning models. You will learn classification, regression, and clustering techniques to work with different types of datasets and train your models.
Matthew Lamons, Rahul Kumar, Abhishek Nagaraja
ISBN 13: 9781788997096 Packt 472 Pages (October 2018)
Book Overview:
Insightful projects to master deep learning and neural network architectures using Python and Keras
Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier.
Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You’ll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system.
Mastering Python for Networking and Security
José Manuel Ortega
ISBN 13: 9781788992510 Packt 426 Pages (September 2018)
Book Overview:
Master Python scripting to build a network and perform security operations
Python is being used for increasingly advanced tasks, with the latest update introducing many new packages. This book focuses on leveraging these updated packages to build a secure network with the help of Python scripting.
This book covers topics from building a network to the different procedures you need to follow to secure it. You’ll first be introduced to different packages and libraries, before moving on to different ways to build a network with the help of Python scripting. Later, you will learn how to check a network’s vulnerability using Python security scripting, and understand how to check vulnerabilities in your network. As you progress through the chapters, you will also learn how to achieve endpoint protection by leveraging Python packages along with writing forensic scripts. By the end of this book, you will be able to get the most out of the Python language to build secure and robust networks that are resilient to attacks.
Jaime Buelta
ISBN 13: 9781789133806 Packt 398 Pages (September 2018)
Book Overview:
Step-by-step instructions which take you through each program to automate monotonous tasks with Python 3.7
The Python Automation Cookbook helps you develop a clear understanding of how to automate your business processes using Python, including detecting opportunities by scraping the web, analyzing information to generate automatic spreadsheets reports with graphs, and communicating with automatically generated emails.
You’ll learn how to get notifications via text messages and run tasks while your mind is focused on other important activities, followed by understanding how to scan documents such as résumés. Once you’ve gotten familiar with the fundamentals, you’ll be introduced to the world of graphs, along with studying how to produce organized charts using Matplotlib. In addition to this, you’ll gain in-depth knowledge of how to generate rich graphics showing relevant information.
Mastering Predictive Analytics with scikit-learn and TensorFlow
Alan Fontaine
ISBN 13: 9781789617740 Packt 154 Pages (September 2018)
Book Overview:
Learn advanced techniques to improve the performance and quality of your predictive models
Python is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems.
This book starts with ensemble methods and their features. You will see that scikit-learn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nitty-gritty of predictive analytics and explore its features and characteristics. You will also be introduced to artificial neural networks and TensorFlow, and how it is used to create neural networks. In the final chapter, you will explore factors such as computational power, along with improvement methods and software enhancements for efficient predictive analytics.
By the end of this book, you will be well-versed in using deep neural networks to solve common problems in big data analysis.
Sam Bowne
ISBN 13: 9781788398343 Packt Course Length: 2 hours 53 minutes (September 2018)
Video Overview:
Create simple binary exploits with Python
This video course starts with high-level code injection, the simplest sort of exploit. It then explains binary exploits that allow you to skip past unwanted code, such as the password or product key tests, and add Trojan code. You will perform the exploit development process: finding a vulnerability, analyzing a crash in a debugger, creating a crafted attack, and achieving remote code execution on Windows and Linux. You will use the gdb debugger to analyze Linux executables and Python code to exploit them. On Windows, you'll use the Immunity debugger and Python.
This course uses a demonstration-and-challenge approach which guides students from passive observation to practical implementation of binary exploit at development techniques.
Python Reinforcement Learning Projects
Sean Saito, Yang Wenzhuo and Rajalingappaa Shanmugamani
ISBN 13: 9781788991612 Packt 296 Pages (September 2018)
Book Overview:
Deploy autonomous agents in business systems using powerful Python libraries and sophisticated reinforcement learning models
Reinforcement learning (RL) is the next big leap in the artificial intelligence domain, given that it is unsupervised, optimized, and fast. Python Reinforcement Learning Projects takes you through various aspects and methodologies of reinforcement learning, with the help of insightful projects.
You will learn about core concepts of reinforcement learning, such as Q-learning, Markov models, the Monte-Carlo process, and deep reinforcement learning. As you make your way through the book, you’ll work on projects with various datasets, including numerical, text, video, and audio, and will gain experience in gaming, image rocessing, audio processing, and recommendation system projects. You’ll explore TensorFlow and OpenAI Gym to implement a deep learning RL agent that can play an Atari game. In addition to this, you will learn how to tune and configure RL algorithms and parameters by building agents for different kinds of games. In the concluding chapters, you’ll get to grips with building self-learning models that will not only uncover layers of data but also reason and make decisions.
By the end of this book, you will have created eight real-world projects that explore reinforcement learning and will have handson experience with real data and artificial intelligence (AI) problems.
Hands-On Markov Models with Python
Ankur Ankan and Abinash Panda
ISBN 13: 9781788625449 Packt 178 Pages (September 2018)
Book Overview:
Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn
Hidden Markov Model (HMM) is a statistical model based on the Markov chain concept. Hands-On Markov Models with Python helps you get to grips with HMMs and different inference algorithms by working on real-world problems. The hands-on examples explored in the book help you simplify the process flow in machine learning by using Markov model concepts, thereby making it accessible to everyone.
Once you’ve covered the basic concepts of Markov chains, you’ll get insights into Markov processes, models, and types with the help of practical examples. After grasping these fundamentals, you’ll move on to learning about the different algorithms used in inferences and applying them in state and parameter inference. In addition to this, you’ll explore the Bayesian approach of inference and learn how to apply it in HMMs.
In further chapters, you’ll discover how to use HMMs in time series analysis and natural language processing (NLP) using Python. You’ll also learn to apply HMM to image processing using 2D-HMM to segment images. Finally, you’ll understand how to apply HMM for reinforcement learning (RL) with the help of Q-Learning, and use this technique for single-stock and multi-stock algorithmic trading.
By the end of this book, you will have grasped how to build your own Markov and hidden Markov models on complex datasets in order to apply them to projects.
Mastering Natural Language Processing with Python (Video)
Deepti Chopra, Iti Mathur, Nisheeth Joshi
ISBN 13: 9781789618358 Packt Course Length: 1 hour 37 minutes (August 2018 )
Video Overview:
Explore various NLP tasks while enhancing your Python skills in real-world scenarios!
This course will give you expertise on how to employ various NLP tasks in Python, giving you an insight into the best practices when designing and building NLP-based applications using Python. It will help you become an expert in no time and assist you in creating your own NLP projects using NLTK. You will sequentially be guided through applying machine learning tools to develop various models. We’ll give you clarity on how to create training data and how to implement major NLP applications such as Named Entity Recognition, Question Answering System, Discourse Analysis, Transliteration, Word Sense disambiguation, Information Retrieval, Text Summarization, and Anaphora Resolution.
Hands-on Supervised Machine Learning with Python (Video)
Taylor Smith
ISBN 13: 9781789347654 Packt Course Length: 3 hours 6 minutes (August 2018)
Video Overview:
Teach your machine to think for itself!
This course will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You’ll embark on this journey with a quick course overview and see how supervised machine learning differs from unsupervised learning.
By the end of the video course, you’ll be equipped with hands-on techniques to gain the practical know-how needed to quickly and powerfully apply these algorithms to new problems.
Real-World Machine Learning Projects with Scikit-Learn [Video]
Nikola Živković
ISBN 13: 9781789131222 Packt Course Length: 2 hours 34 minutes (August 2018)
Video Overview:
Predict heart disease, customer-buying behaviors, and much more in this course filled with real-world projects
Scikit-Learn is one of the most powerful Python Libraries with has a clean API, and is robust, fast and easy to use. It solves real-world problems in the areas of health, population analysis, and figuring out buying behavior, and more.
In this course you will build powerful projects using Scikit-Learn. Using algorithms, you will learn to read trends in the market to address market demand. You'll delve more deeply to decode buying behavior using Classification algorithms; cluster the population of a place to gain insights into using K-Means Clustering; and create a model using Support Vector Machine classifiers to predict heart disease.
Beginning Selenium WebDriver Testing in Python
Andy Craze
ISBN 13: 9781789138580 Packt Course Length: 1 hour 47 minutes (August 2018)
Video Overview:
Use Selenium automation, to save you time when testing in Python
This course introduces Python users to Selenium WebDriver. It will help users with basic programming knowledge to start code-testing. This course will help users cut down on their time spent on testing code written in Python.
ou will then start practicing the basics. Next, you will explore the biggest strength of Selenium: integrating your test instances with the browser of your choice. You will then actually test an authentication system in a sequential manner by following each of the required steps. By the end of the course, you will be able to provide your customers and clients with better quality code in less time, enhancing customer satisfaction!
Alvaro Fuentes
ISBN 13: 9781789531701 Packt 178 Pages (August 2018)
Book Overview:
Enhance your data analysis and predictive modeling skills using popular Python tools
In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques.
By the end of this book, you will have hands-on experience performing data analysis with Python.
Hands-On Bitcoin Programming with Python
Harish Kumar Garg
ISBN 13: 9781789537000 Packt 90 Pages (August 2018)
Book Overview:
Simplified Python programming for Bitcoin and Blockchain
Bitcoin is a cryptocurrency that’s changing the face of online payments. Hands-On Bitcoin Programming with Python teaches you to build software applications for mining and creating Bitcoins using Python.
This book starts with the basics of both Bitcoin and blockchain and gives you an overview of these inherent concepts by showing you how to build Bitcoin-driven applications with Python. Packed with clear instructions and practical examples, you will learn to understand simple Python coding examples that work with this cryptocurrency.
Applied Deep Learning with Python
Alex Galea and Luis Capelo
ISBN 13: 9781789804744 Packt 334 Pages (August 2018)
Book Overview:
A hands-on guide to deep learning that’s filled with intuitive explanations and engaging practical examples
aking an approach that uses the latest developments in the Python ecosystem, you’ll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. We’ll explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. It’s okay if these terms seem overwhelming; we’ll show you how to put them to work.
We’ll build upon our classification coverage by taking a quick look at ethical web scraping and interactive visualizations to help you professionally gather and present your analysis. It’s after this that we start building out our keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data.
Modern Python Standard Library Cookbook
Alessandro Molina
ISBN 13: 9781788830829 Packt 366 Pages (August 2018)
Book Overview:
Build optimized applications in Python by smartly implementing the standard library
The Python 3 Standard Library is a vast array of modules that you can use for developing various kinds of applications. It contains an exhaustive list of libraries, and this book will help you choose the best one to address specific programming problems in Python.
The Modern Python Standard Library Cookbook begins with recipes on containers and data structures and guides you in performing effective text management in Python. You will find Python recipes for command-line operations, networking, filesystems and directories, and concurrent execution. You will learn about Python security essentials in Python and get to grips with various development tools for debugging, benchmarking, inspection, error reporting, and tracing. The book includes recipes to help you create graphical user interfaces for your application. You will learn to work with multimedia components and perform mathematical operations on date and time. The recipes will also show you how to deploy different searching and sorting algorithms on your data.
Mariano Anaya
ISBN 13: 9781788835831 Packt 332 Pages (August 2018)
Book Overview:
Getting the most out of Python to improve your codebase
The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into object oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform.
By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code.
PyCharm for Power-Developer (Video)
Melissa Dale
ISBN 13: 9781788835794 Packt Course Length: 2 hours 13 minutes (August 2018)
Video Overview:
Optimize Pycharm's strength to develop application easily.
In this course, you’ll learn how to improve your code quality with Lens Mode and Intentions, refactor and debug code, and perform unit testing with the PyCharm test runner. Along the way, we’ll work with SQL databases. Further on, you’ll learn to integrate Python with web projects that include HTML and JavaScript and build a project with the Flask microframework.
By the end of the course, you’ll be well-versed with a terrific tool for Python development—PyCharm—and be able to do everything expected of a Python developer.
Bruno Oliveira
ISBN 13: 9781789347562 Packt 160 Pages (August 2018)
Book Overview:
Learn the pytest way to write simple tests which can also be used to write complex tests
Python's standard unittest module is based on the xUnit family of frameworks, which has its origins in Smalltalk and Java, and tends to be verbose to use and not easily extensible.The pytest framework on the other hand is very simple to get started, but powerful enough to cover complex testing integration scenarios, being considered by many the true Pythonic approach to testing in Python.
In this book, you will learn how to get started right away and get the most out of pytest in your daily workflow, exploring powerful mechanisms and plugins to facilitate many common testing tasks. You will also see how to use pytest in existing unittest-based test suites and will learn some tricks to make the jump to a pytest-style test suite quickly and easily.
Mastering Python Networking - Second Edition
Eric Chou
ISBN 13: 9781789135992 Packt 466 Pages (August 2018)
Book Overview:
Master the art of using Python for a diverse range of network engineering tasks
Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In this second edition of Mastering Python Networking, you’ll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks.
This book begins by reviewing the basics of Python and teaches you how Python can interact with both legacy and API-enabled network devices. As you make your way through the chapters, you will then learn to leverage high-level Python packages and frameworks to perform network engineering tasks for automation, monitoring, management, and enhanced security. In the concluding chapters, you will use Jenkins for continuous network integration as well as testing tools to verify your network.
Hands-On Natural Language Processing with Python
Rajesh Arumugam, Rajalingappaa Shanmugamani
ISBN 13: 9781789139495 Packt 312 Pages (July 2018)
Book Overview:
Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow
Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges.
To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow.
Hands-On Recommendation Systems with Python
Rounak Banik
ISBN 13: 9781788993753 Packt 146 Pages (July 2018)
Book Overview:
With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web
This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—you'll get started with building and learning about recommenders as quickly as possible..
In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques
With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains.
Getting Started with Modern Python (Video)
Joran Beasley
ISBN 13: 9781788472784 Packt Course Length: 3 hours 16 minutes (July 2018)
Video Overview:
Learn Python like a Professional! Start from the basics and go all the way to create your program in it.
In this course, you will start by setting up your development environment, including downloading Python and setting up your IDE (PyCharm); you'll then be introduced to Python lists and list comprehensions. The course will then show you what a generator is and why you might want to use one. Further on, you will be introduced to functions and decorators, and see how you can use them. You will then learn how to create a very simple, single-file Python program, and how to execute it both from the command line and from within the IDE. You'll also get a very brief introduction to debugging.
By the end of the course, you'll have learned how to manipulate strings, parsing and printing them.
Building REST APIs with Python (Video)
Wayne Merry
ISBN 13: 9781788293143 Packt Course Length: 2 hours 49 minutes (July 2018)
Video Overview:
Take your skills with Python to the next level by guiding you to pick the right stack.
With the growing demand for full-stack developers, it is important to learn how you can combine the powers of Python with other libraries to create amazing applications.
Django has basic front-end support but we show how complex operations can be performed at the front-end. We show you how to unleash the power of Python's Rest API and other functionalities to create compelling applications powered by ReactJS.
We will be using a production-level database such as Postgres. Delving into key aspects such as code reusability, deployment and maintaining your application, we discuss production server configuration and bundle technologies with Python to provide an end-to-end web development solution.
Python Tips, Tricks and Techniques (Video)
Colibri Ltd
ISBN 13: 9781789138535 Packt Course Length: 2 hours and 38 minutes (July 2018)
Video Overview:
From first-class functions to abstract base classes, apply Pythonic tricks to your application and be a Python rockstar
This course is will take you from a Python outsider to an insider. You will benefit from insights from the Python documentation, PEPs, and online developer communities to learn the ultimate Pythonic ways to tackle common programming patterns. This course covers tips, tricks, and techniques for loops, data structures, object-oriented programming, functions, and more, helping you work on ordered collections and key-value stores for dictionaries. You will be able to increase the speed and performance of your code while making it easier to debug. Start writing cleaner code for your applications and learn to organize it better in just 3 hours.
he course is full of hands-on instructions, interesting and illustrative visualizations, and clear explanations. It is packed full of useful tips and relevant advice which can be applied to real, commercial products. Throughout the course, we maintain a focus on practicality and getting things done, not fancy programming concepts and theory.
Tips, Tricks, and Techniques for Python Application Development (Video)
Mihai Costea
ISBN 13: 9781789139235 Packt Course Length: 3 hours 17 minutes (July 2018)
Video Overview:
Improve your application development process to build efficient apps with Python
The course starts by dealing with performance issues and learning how to tackle them in an application. Distributing an application with Python is not easy but you will learn ways to distribute applications developed using Python along with GUIs, web applications, and more. Further, you will learn to test your application at different levels and use modern software at the development stage. You will also learn to expand productivity using standard and third-party tools. Finally, you will learn to protect your code quality from potential errors and detect any problem at an early stage, to prevent any issues later.
You will start by exploring Python issues and how to diagnose them. Then you will be introduced to the most popular ways to distribute Python applications. Next, you will test applications and use modern software in the development process. Finally, you will learn to expand your productivity and manage code quality to prevent any issues later.
Troubleshooting Python Application Development (Video)
Rudy Lai
ISBN 13: 9781788995337 Packt Course Length: 2 hours 50 minutes (July 2018)
Video Overview:
Tackle Python performance problems and speed up your apps with parallelism, concurrent execution, and OOP
Troubleshooting Python Application Development is your answer. This course takes you through a structured journey of performance problems that your application is likely to encounter, and presents both the intuition and the solution to these issues. You'll get things done, without a lengthy detour into how Python is implemented or computational theory.
The course is full of hands-on instructions, interesting and illustrative visualizations, and, clear explanations from a data scientist. It is packed full of useful tips and relevant advice. Throughout the course, we maintain a focus on practicality and getting things done, not fancy mathematical theory.
Hands-on Network Programming with Python {Video}
Eric Chou
ISBN 13: 9781788994583 Packt XXX Pages OR Course Length: 3 hours 3 minutes (July 2018)
Video Overview:
The complete guide that will help you create and automate your network with Python
The goal of the course is to master key Python concepts as they are applied in the network engineering context. Computer Networks, large and small, has become ever increasingly software-driven in the last several years. A typical network engineer faces the challenge of learning a completely new discipline that normally takes years to master. This course will use Python, an easy-to-learn, popular first-time-programmer language as the foundation to bridge the gap for network engineers facing the automation challenge, this will help network engineers become experts in using Python for networking.
The video will start by demonstrating how to use Python and supported libraries to automate network tasks. Then you will get familiar with the concepts and work with the Ansible framework in order to achieve your network goals. You will then come across ways to monitor your network using Python. Besides this, you will develop a good understanding and explore ways to solve issues related to the security wheel that treats the network as one single entity instead of dispersing components. By the end of the course, the students will master skills required to accomplish advance network automation using Python.
Hands-on NLP with NLTK and Scikit-learn {Video}
Colibri Ltd
ISBN 13: 9781789345612 Packt Course Length: 2 hours 46 minutes (July 2018)
Video Overview:
A complete Python guide to Natural Language Processing to build spam filters, topic classifiers, and sentiment analyzers
There is an overflow of text data online nowadays. As a Python developer, you need to create a new solution using Natural Language Processing for your next project. Your colleagues depend on you to monetize gigabytes of unstructured text data. What do you do?
Hands-on NLP with NLTK and scikit-learn is the answer. This course puts you right on the spot, starting off with building a spam classifier in our first video. At the end of the course, you are going to walk away with three NLP applications: a spam filter, a topic classifier, and a sentiment analyzer. There is no need for fancy mathematical theory, just plain English explanations of core NLP concepts and how to apply those using Python libraries. Taking this course will help you to precisely create new applications with Python and NLP. You will be able to build actual solutions backed by machine learning and NLP processing models with ease.
Data Science Essentials Advanced Algorithms and Visualizations (Video)
Alberto Boschetti, Luca Massaron
ISBN 13: 9781789616057 Packt Course Length: 1 hours 50 minutes (July 2018)
Video Overview:
Become an efficient data science practitioner by understanding Python's key concepts
This course will make you look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. We start with SVM and random forest for classification and regression. We look at big data, deep learning, and language processing.
Then we use graph analysis techniques for very interesting and trending social media analytics. Finally, we take a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment tools that make it easier to present your results to an audience of both data science experts and business users.
Statistical Methods and Applied Mathematics in Data Science (Video)
Cyrille Rossant
ISBN 13: 9781789539219 Packt Course Length: 2 hours 38 minutes (July 2018)
Video Overview:
Use IPython and Jupyter Notebook to sharpen your skills for your data analysis and visualization tasks
Machine learning and data analysis are the center of attraction for many engineers and scientists. The reason is quite obvious: its vast application in numerous fields and booming career options. And Python is one of the leading open source platforms for data science and numerical computing. IPython, and its associated Jupyter Notebook, provide Python with efficient interfaces to for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. If you are among those seeking to enhance their capabilities in machine learning, then this course is the right choice.
Statistical Methods and Applied Mathematics in Data Science provides many easy-to-follow, ready-to-use, and focused recipes for data analysis and scientific computing. This course tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.
Qt5 Python GUI Programming Cookbook
B.M. Harwani
ISBN 13: 9781788831000 Packt 462 Pages (July 2018)
Book Overview:
Over 60 recipes to help you design interactive, smart, and cross-platform GUI applications
PyQt is one of the best cross-platform interface toolkits currently available; it's stable, mature, and completely native. If you want control over all aspects of UI elements, PyQt is what you need. This book will guide you through every concept necessary to create fully functional GUI applications using PyQt, with only a few lines of code.
As you expand your GUI using more widgets, you will cover networks, databases, and graphical libraries that greatly enhance its functionality. Next, the book guides you in using Qt Designer to design user interfaces and implementing and testing dialogs, events, the clipboard, and drag and drop functionality to customize your GUI. You will learn a variety of topics, such as look and feel customization, GUI animation, graphics rendering, implementing Google Maps, and more.
Building Machine Learning Systems with Python - Third Edition
Luis Pedro Coelho, Willi Richert, Matthieu Brucher
ISBN 13: 9781788623223 Packt 406 Pages (July 2018)
Book Overview:
Get more from your data by creating practical machine learning systems with Python
This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you’ll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems.
By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks.
Building Serverless Python Web Services with Zappa
Abdulwahid Abdulhaque Barguzar
ISBN 13: 9781788837613 Packt 324 Pages (July 2018)
Book Overview:
Master serverless architectures in Python and their implementation, with Zappa on three different frameworks.
Serverless applications are becoming very popular these days, not just because they save developers the trouble of managing the servers, but also because they provide several other benefits such as cutting heavy costs and improving the overall performance of the application.
This book will help you build serverless applications in a quick and efficient way. We begin with an introduction to AWS and the API gateway, the environment for serverless development, and Zappa. We then look at building, testing, and deploying apps in AWS with three different frameworks--Flask, Django, and Pyramid. Setting up a custom domain along with SSL certificates and configuring them with Zappa is also covered. A few advanced Zappa settings are also covered along with securing Zappa with AWS VPC.
Denny Lee, Tomasz Drabas
ISBN 13: 9781788835367 Packt 330 Pages (June 2018)
Book Overview:
Combine the power of Apache Spark and Python to build effective big data applications
You’ll start by learning the Apache Spark architecture and how to set up a Python environment for Spark. You’ll then get familiar with the modules available in PySpark and start using them effortlessly. In addition to this, you’ll discover how to abstract data with RDDs and DataFrames, and understand the streaming capabilities of PySpark. You’ll then move on to using ML and MLlib in order to solve any problems related to the machine learning capabilities of PySpark and use GraphFrames to solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command.
By the end of this book, you will be able to use the Python API for Apache Spark to solve any problems associated with building data-intensive applications.
Hands-On Reinforcement Learning with Python
Sudharsan Ravichandiran
ISBN 13: 9781788836524 Packt 318 Pages (June 2018)
Book Overview:
A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python
The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning.
By the end of the book, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence.
Mastering Numerical Computing with NumPy
Umit Mert Cakmak, Mert Cuhadaroglu
ISBN 13: 9781788993357 Packt 248 Pages (June 2018)
Book Overview:
Enhance the power of NumPy and start boosting your scientific computing capabilities
Beginning with NumPy's arrays and functions, you will familiarize yourself with linear algebra concepts to perform vector and matrix math operations. You will thoroughly understand and practice data processing, exploratory data analysis (EDA), and predictive modeling. You will then move on to working on practical examples which will teach you how to use NumPy statistics in order to explore US housing data and develop a predictive model using simple and multiple linear regression techniques. Once you have got to grips with the basics, you will explore unsupervised learning and clustering algorithms, followed by understanding how to write better NumPy code while keeping advanced considerations in mind. The book also demonstrates the use of different high-performance numerical computing libraries and their relationship with NumPy. You will study how to benchmark the performance of different configurations and choose the best for your system.
By the end of this book, you will have become an expert in handling and performing complex data manipulations.
Learn Python Programming - Second Edition
Fabrizio Romano
ISBN 13: 9781788996662 Packt 508 Pages (June 2018)
Book Overview:
Build a solid foundation in coding by utilizing the language and its core characteristics
You will begin by exploring the foundations of and fundamental topics on Python and learn to manipulate them. Then, you'll explore different programming paradigms that will allow you to find the best approach to a situation, and you’ll also understand how to carry out performance optimization as well as effective debugging. As you make your way through the chapters, you'll control the flow of a program, and persist and utilize an interchange format to exchange data. You'll also walk through cryptographic services in Python and understand secure tokens.
Throughout, the book covers various types of applications, and it concludes with building real-world applications based on all the concepts that you learned. By the end of the book, you'll have a proper understanding of the Python language and a solid grasp on how to work with data. You'll know how to quickly build a website and harness the power of Python's renowned data science libraries.
Hands-On Enterprise Automation with Python
Basim Aly
ISBN 13: 9781788998512 Packt 398 Pages (June 2018)
Book Overview:
Invent your own Python scripts to automate your infrastructure
We’ll explore examples of network automation tasks using simple Python programs and Ansible. Next, we will walk you through automating administration tasks with Python Fabric, where you will learn to perform server configuration and administration, along with system administration tasks such as user management, database management, and process management. As you progress through this book, you’ll automate several testing services with Python scripts and perform automation tasks on virtual machines and cloud infrastructure with Python. In the concluding chapters, you will cover Python-based offensive security tools and learn how to automate your security tasks.
By the end of this book, you will have mastered the skills of automating several system administration tasks with Python.
Mastering Machine Learning for Penetration Testing
Chiheb Chebbi
ISBN 13: 9781788997409 Packt 276 Pages (June 2018)
Book Overview:
Become a master at penetration testing using machine learning with Python
This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you’ve gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you’ll see how to find loopholes and surpass a self-learning security system.
As you make your way through the chapters, you’ll focus on topics such as network intrusion detection and AV and IDS evasion. We’ll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system.
By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system
Deep Learning Projects with PyTorch (Video)
Ashish Singh Bhatia
ISBN 13: 9781788997591 Packt Course Length: 3 hours (June 2018)
Video Overview:
Step into the world of PyTorch to create deep learning models with the help of real-world examples
PyTorch is a Deep Learning framework that is a boon for researchers and data scientists. It supports Graphic Processing Units and is a platform that provides maximum flexibility and speed. With PyTorch, you can dynamically build neural networks and easily perform advanced Artificial Intelligence tasks.
The course starts with the fundamentals of PyTorch and how to use basic commands. Next, you’ll learn about Convolutional Neural Networks (CNN) through an example of image recognition, where you’ll look into images from a machine perspective.
The next project shows you how to predict character sequence using Recurrent Neural Networks (RNN) and Long Short Term Memory Network (LSTM). Then you’ll learn to work with autoencoders to detect credit card fraud. After that, it’s time to develop a system using Boltzmann Machines, where you’ll recommend whether to watch a movie or not.
We’ll continue with Boltzmann Machines, where you’ll learn to give movie ratings using AutoEncoders. In the end, you’ll get to develop and train a model to recognize a picture or an object from a given image using Deep Learning, where we’ll not only detect the shape, but also the color of the object.
By the end of the course, you’ll be able to start using PyTorch to build Deep Learning models by implementing practical projects in the real world. So, grab this course as it will take you through interesting real-world projects to train your first neural nets.
Computer Vision Projects with Python 3 (Video)
Matthew Rever
ISBN 13: 9781788835565 Packt Course Length: 2 hours 19 minutes (June 2018)
Video Overview:
Explore Python’s powerful tools for extracting data from images and videos
The Python programming language is an ideal platform for rapidly prototyping and developing production-grade codes for image processing and computer vision with its robust syntax and wealth of powerful libraries.
This video course will start by showing you how to set up Anaconda Python for the major OSes with cutting-edge third-party libraries for computer vision. You’ll learn state-of-the-art techniques to classify images and find and identify humans within videos.
Next, you’ll understand how to set up Anaconda Python 3 for the major OSes (Windows, Mac, and Linux) and augment it with the powerful vision and machine learning tools OpenCV and TensorFlow, as well as Dlib. You’ll be taken through the handwritten digits classifier and then move on to detecting facial features and finally develop a general image classifier.
By the end of this course, you’ll know the basic tools of computer vision and be able to put it into practice.
Beginning Data Science with Python And Jupyter
Alex Galea
ISBN 13: 9781789532029 Packt 194 Pages (June 2018)
Book Overview:
Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction.
Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context.
Learning Python Web Penetration Testing
Christian Martorella
ISBN 13: 9781789533972 Packt 138 Pages (June 2018)
Book Overview:
Leverage the simplicity of Python and available libraries to build web security testing tools for your application
Learning Python Web Penetration Testing will walk you through the web application penetration testing methodology, showing you how to write your own tools with Python for each activity throughout the process. The book begins by emphasizing the importance of knowing how to write your own tools with Python for web application penetration testing.
You will then learn to interact with a web application using Python, understand the anatomy of an HTTP request, URL, headers and message body, and later create a script to perform a request, and interpret the response and its headers. As you make your way through the book, you will write a web crawler using Python and the Scrappy library. The book will also help you to develop a tool to perform brute force attacks in different parts of the web application.
Learning Robotics using Python - Second Edition
Lentin Joseph
ISBN 13: 9781788623315 Packt 280 Pages (June 2018)
Book Overview:
Design, simulate, and program interactive robots
Robot Operating System (ROS) is one of the most popular robotics software frameworks in research and industry. It has various features for implementing different capabilities in a robot without implementing them from scratch.
This book starts by showing you the fundamentals of ROS so you understand the basics of differential robots. Then, you'll learn about robot modeling and how to design and simulate it using ROS. Moving on, we'll design robot hardware and interfacing actuators. Then, you'll learn to configure and program depth sensors and LIDARs using ROS. Finally, you'll create a GUI for your robot using the Qt framework.
By the end of this tutorial, you'll have a clear idea of how to integrate and assemble everything into a robot and how to bundle the software package.
Python Testing Cookbook - Second Edition
Greg L. Turnquist, Bhaskar N. Das
ISBN 13: 9781787122529 Packt 396 Pages (June 2018)
Book Overview:
Fix everyday testing problems in Python with the help of this solution-based guide
Automated testing is the best way to increase efficiency while reducing the defects of software testing. It helps find bugs in code easily and at an early stage so that they can be tackled efficiently. This book delves into essential testing concepts used in Python to help you build robust and maintainable code.
Python Testing Cookbook begins with a brief introduction to Python's unit testing framework to help you write automated test cases. You will learn how to write suitable test sets for your software and run automated test suites with Nose. You will then work with the unittest.mock library, which allows you to replace the parts of your system that are being tested with mock objects and make assertions about how they have been used. You will also see how to apply Test-driven Development (TDD) and Behavior-driven Development (BDD) and how to eliminate issues caused by TDD. The book explains how to integrate automated tests using Continuous Integration and perform smoke/load testing. It also covers best practices and will help you solve persistent testing issues in Python. The book concludes by helping you understand how doctest works and how Selenium can be used to test code efficiently.
Python Machine Learning in 7 Days (Video)
Arish Ali
ISBN 13: 9781788999137 Packt Course Length: 2 hours 22 minutes (June 2018)
Video Overview:
Build powerful Machine Learning models using Python with hands-on practical examples in just a week.
Machine learning is one of the most sought-after skills in the market. But have you ever wondered where to start or found the course not so easy to follow. With this hands-on and practical machine learning course, you can learn and start applying machine learning in less than a week without having to be an expert mathematician.
In this course, you will be introduced to a new machine learning aspect in each section followed by a practical assignment as a homework to help you in efficiently implement the learnings in a practical manner. With the systematic and fast-paced approach to this course, learn machine learning using Python in the most practical and structured way to develop machine learning projects in Python in a week.
This course is structured to unlock the potential of Python machine learning in the shortest amount of time. If you are looking to upgrade your machine learning skills using Python in the quickest possible time, then this course is for you!
Hands-On Unsupervised Learning with Python (Video)
Stefan Jansen
ISBN 13: 9781788992855 Packt Course Length: 3 hours 34 minutes (June 2018)
Video Overview:
Use Python to apply market basket analysis, PCA and dimensionality reduction, as well as cluster algorithms
This course explains the most important Unsupervised Learning algorithms using real-world examples of business applications in Python code.
Say you have millions of transaction data on products purchased at a retailer. Which individual products or product categories are most likely to be purchased together? How about a large number of survey responses – which answers were most often given together, for all or some subset of respondents? Association Rules provide answers to these questions, and they are most frequently used in Market Basket Analysis. The Apriori Algorithms solves the formidable computational challenges of calculating Association Rules. After taking this course, you will be understanding and be able to apply the Apriori Algorithm to calculate, interpret and create interactive visualizations of association rules.
This course will allow you to utilize Principal Component Analysis, and to visualize and interpret the results of your datasets such as the ones in the above description. You will also be able to apply hard and soft clustering methods (k-Means and Gaussian Mixture Models) to assign segment labels to customers categorized in your sample data sets.
Learn Python in 3 Hours (Video)
Rudy Lai
ISBN 13: 9781788995931 Packt Course Length: 2 hours 36 minutes (June 2018)
Video Overview:
App development, data science, automation, web scraping or computer vision—Make the switch to Python quickly
You are a programmer. You already know many languages, but Python isn't one of them. Today, you need to get up-to-speed with Python in a short period of time, but your search has so far come up with disconnected, unrelated tutorials or guides.
Learn Python in 3 hours is a fast-paced, action-packed course that maximizes your time; it's designed from the ground up to bring you from zero to hero in the shortest time. The course is based on many years of Python development experience in both large enterprises and nimble startups. In particular, the course's hands-on and practical approach comes from the author's experience in rapidly iterating and shipping products in a startup setting, where responsiveness and speed are key.
With Learn Python in 3 hours, you will be up-and-running with Python like you are with your other languages, proving your value and expertise to your team today, and building your CV and skillset for tomorrow
Python Deep Learning Solutions (Video)
Indra den Bakker
ISBN 13: 9781789531602 Packt Course Length: 1 hour 45 minutes (June 2018)
Video Overview:
Over 20 practical videos on neural network modeling, reinforcement learning, and transfer learning using Python
Deep Learning is revolutionizing a wide range of industries. For many applications, Deep Learning has been proven to outperform humans by making faster and more accurate predictions. This course provides a top-down and bottom-up approach to demonstrating Deep Learning solutions to real-world problems in different areas.
These applications include Computer Vision, Generative Adversarial Networks, and time series. This course presents technical solutions to the issues presented, along with a detailed explanation of the solutions.
Furthermore, it provides a discussion on the corresponding pros and cons of implementing the proposed solution using a popular framework such as TensorFlow, PyTorch, and Keras. The course includes solutions that are related to the basic concepts of neural networks; all techniques, as well as classical network topologies, are covered. The main purpose of this video course is to provide Python programmers with a detailed list of solutions so they can apply Deep Learning to common and not-so-common scenarios.
2018 Python Regular Expressions - Real World Projects (Video)
Chandra Lingam
ISBN 13: 9781789539523 Packt Course Length: 3 hours 10 minutes (June 2018)
Video Overview:
Learn cutting-edge pattern matching skills for log mining, big data parsing, cleanup and preparation with Regex
Welcome to Python Regular Expressions Course! You will apply your new skills with four hands-on real-world projects. You will gain solid understanding on type of performance issues regex can run into, and techniques to address them. As part of resources in this course, you will get a high-quality quick reference guide, an interactive tool, all the source code and downloadable slides. Why Learn Regular Expressions? Very often, the data that we need is not readily accessible or useful.
Data preparation and clean-up is often one of the most time-consuming activities in a software automation project. Instead of spending time writing code for all this, you can specify data patterns of interest and let regular expression engine do the work for you. Regular Expression is cross-platform and you can learn the concepts once and use it in multiple programming languages and environment Looking forward to seeing you in the course! God Speed!
Python Machine Learning Tips, Tricks, and Techniques (Video)
Valeriy Babushkin
ISBN 13: 9781789135817 Packt Course Length: 2 hours 46 minutes (June 2018)
Video Overview:
Transform your simple machine learning model into a cutting edge powerful version
Machine learning allows us to interpret data structures and fit that data into models to identify patterns and make predictions. Python makes this easier with its huge set of libraries that can be easily used for machine learning. In this course, you will learn from a top Kaggle master to upgrade your Python skills with the latest advancements in Python.
Each technique we cover is itself enough to improve your results. However; combining them together is where the real magic is. Throughout the course, you will work on real datasets to increase your expertise and keep adding new tools to your machine learning toolbox.
By the end of this course, you will know various tips, tricks, and techniques to upgrade your machine learning algorithms to reduce common problems, all the while building efficient machine learning models.
Natural Language Processing with TensorFlow
Thushan Ganegedara
ISBN 13: 9781788478311 Packt 472 Pages (May 2018)
Book Overview:
Write modern natural language processing applications using deep learning algorithms and TensorFlow.
Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator.
After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks.
Data Visualization Recipes in Python (Video)
Theodore Petrou
ISBN 13: 9781789340495 Packt Course Length: 1 hours 43 minutes (MAY 2018)
Video Overview:
Utilize Python’s most efficient libraries—pandas, matplotlib, and Seaborn—for data visualization and time series analysis
Visualization is a critical component in exploratory data analysis, as well as presentations and applications. If you are struggling in your day-to-day data analysis tasks, then this is the right course for you. This fast-pace guide follows a recipe-based approach, each video focusing on a commonly-faced issue.
This course covers advanced and powerful time series capabilities so you can dissect by any possible dimension of time. It introduces the Matplotlib library, which is responsible for all of the plotting in pandas, at the same time focusing on the pandas plot method and the Seaborn library, which is capable of producing aesthetically pleasing visualizations not directly available in pandas. This course guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter.
Hands-On Data Science with Anaconda
Dr. Yuxing Yan, James Yan
ISBN 13: 9781788831192 Packt 364 Pages (May 2018)
Book Overview:
Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda
Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world.
The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod.
Diwakar Vaish
ISBN 13: 9781788832922 Packt 340 Pages (May 2018)
Book Overview:
Leverage the power of python to build DIY robotic projects
Robotics is a fast-growing industry. Multiple surveys state that investment in the field has increased tenfold in the last 6 years, and is set to become a $100-billion sector by 2020. Robots are prevalent throughout all industries, and they are all set to be a part of our domestic lives. This book starts with the installation and basic steps in configuring a robotic controller.
You'll then move on to setting up your environment to use Python with the robotic controller. You'll dive deep into building simple robotic projects, such as a pet-feeding robot, and more complicated projects, such as machine learning enabled home automation system (Jarvis), vision processing based robots and a self-driven robotic vehicle using Python.
Secret Recipes of the Python Ninja
Cody Jackson
ISBN 13: 9781788294874 Packt 380 Pages (MAY 2018)
Book Overview:
Test your Python programming skills by solving real-world problems
This book covers the unexplored secrets of Python, delve into its depths, and uncover its mysteries. You’ll unearth secrets related to the implementation of the standard library, by looking at how modules actually work. You’ll understand the implementation of collections, decimals, and fraction modules. If you haven’t used decorators, coroutines, and generator functions much before, as you make your way through the recipes, you’ll learn what you’ve been missing out on.
We’ll cover internal special methods in detail, so you understand what they are and how they can be used to improve the engineering decisions you make. Next, you’ll explore the CPython interpreter, which is a treasure trove of secret hacks that not many programmers are aware of. We’ll take you through the depths of the PyPy project, where you’ll come across several exciting ways that you can improve speed and concurrency.
Deep learning for NLP using Python (Video)
Tyler Edwards
ISBN 13: 9781788621700 Packt Course Length: 1 hours 51 minutes (May 2018)
Video Overview:
Learn how to apply the concepts of deep learning to a diverse range of natural language processing (NLP) techniques
In this course, you’ll expand your NLP knowledge and skills while implementing deep learning tools to perform complex tasks. You’ll start by preparing your environment for NLP and then quickly learn about language structure and how we can break sentences down to extract information and uncover the underlying meaning. After reviewing the basics, we’ll move on to speech recognition and show how deep learning can be used to build speech recognition applications.
By the end of this tutorial, you’ll have a better understanding of NLP and will have worked on multiple examples that implement deep learning to solve real-world spoken language problems. In particular, you’ll be able to discover useful information and extract key insights from piles of natural language data.
Getting Started with Object-Oriented Programming in Python 3 (Video)
Indrasen Pilankar
ISBN 13: 9781788629744 Packt Course Length: 2 hours 26 minutes (May 2018)
Video Overview:
A practical approach to Object-Oriented Programming (OOP) in Python 3.
The world is filled with coders, who write pieces of programs in a bid to find solutions to various problems. In such a field where the competition is already intense, you need a definitive edge over the rest. One of the better ways to stay ahead of the pack is to write smarter code. Writing large programs can be painful. That’s where Object-Oriented Programming (OOP) comes to the rescue. OOP saves a considerable amount of coding man-hours in the long run by writing code in a smarter way, through various techniques.
To ensure efficient coding, you will be introduced to Exceptions and Error Handling. Furthermore, Encapsulation with methods and variables will help you to keep data safe from external, unwanted interference. In the final sections, you will be taken through recursion mechanisms.
By the end of this course, you will be well-versed with the OOP techniques in Python 3, which will help you to write codes better and in an efficient manner.
Modeling and Visualization of Data in Pandas (Video)
Prabhat Ranjan
ISBN 13: 9781788471312 Packt Course Length: 1 hour 21 minutes (May 2018)
Video Overview:
Learn how to model and visualize data in Python through Pandas data library
This video course will support users as they work through a typical real-world data analysis project step-by-step using Pandas. It develops the deep knowledge and skills that will enable students to immediately tackle their own projects with Pandas at work.
This product demonstrates how to make financial models using Python's software library for data manipulation and analysis.
Burkhard Meier
ISBN 13: 9781788625807 Packt Course Length: 3 hours 20 minutes (May 2018)
Video Overview:
Practical coding projects to get you up and running with Python in no time
This video course explores Python basics, data structures, and algorithms. We'll build a die rolling simulator to see how to use Python dictionaries, loops, functions, and control statements.
Next we will use a modular approach to build a game that consists of a deck of playing cards. We will use object-oriented (OOP) Python classes to do so. We will display the playing cards both in a textual form, which we create, as well as via image files. This will lead to our displaying card images in a graphical form using Python's built-in Tkinter package.
Applications of Statistical Learning with Python (Video)
Curtis Miller
ISBN 13: 9781788295499 Packt Course Length: 1 hours 44 minutes (May 2018)
Video Overview:
Turn practical hands-on projects such as language processing, computer vision, sentiment analysis, and text processing into useful application in Python to take your skills to another level!
You’ll learn to read text in documents using different models, and employ sentiment analysis to predict the author’s intent. You’ll also see how to employ Python to read images and for computer vision. Once you’ve learned to employ specific Python packages and syntax for these tasks, you’ll explore case studies that put forth solid real-world examples on spam filtering and analyzing human emotions through a dictionary of images.
This course contains in-depth content balanced with tutorials that put theory into practice. This course will give you both a theoretical understanding and practical exp with examples that will allow you indulge in the art of statistical modeling and analysis using the Python programming language.
Machine Learning for OpenCV – Advanced Methods and Deep Learning (Video)
Michael Beyeler
ISBN 13: 9781789340525 Packt Course Length: 2 hours and 25 minutes (May 2018)
Video Overview:
A practical introduction to the world of machine learning and image processing using OpenCV and Python
This course will cover essential concepts such as classifiers and clustering and will also help you get acquainted with neural networks and Deep Learning to address real-world problems.
The course will also guide you through creating custom graphs and visualizations, and show you how to go from raw data to beautiful visualizations. By the end of this course, you will be ready to create your own ML system and will also be able to take on your own machine learning problems.
Hands-On Test Driven Development with Python (Video)
Richard Wells
ISBN 13: 9781789138313 Packt Course Length: 2 hours and 18 minutes (May 2018)
Video Overview:
Apply the practices of Test-Driven Development using the PyTest framework to easily create your unit tests
In this video tutorial, you’ll learn about the PyTest testing library and how it’s used to write unit tests in Python. You’ll also set up some common Python development environments to use PyTest. You’ll create isolated test environments with Test Doubles and learn how to implement and use them with unittest.mock. Moving on, you’ll get to know some of the best practices in Unit Testing and TDD and get some hands-on experience with programming by implementing unit tests using TDD in Python.
By the end of this course, you’ll be able to apply the practices of Unit Testing and TDD on a daily basis to radically increase the quality of your code and help you and your company achieve your goals faster than ever before.
Hands-On MQTT Programming with Python
Gastón C. Hillar
ISBN 13: 9781789138542 Packt 228 Pages (May 2018)
Book Overview:
Explore the features included in the latest versions of MQTT for IoT and M2M communications and use them with modern Python 3.
MQTT is a lightweight messaging protocol for small sensors and mobile devices. This book explores the features of the latest versions of MQTT for IoT and M2M communications, how to use them with Python 3, and allow you to interact with sensors and actuators using Python.
The book begins with the specific vocabulary of MQTT and its working modes, followed by installing a Mosquitto MQTT broker. You will use different utilities and diagrams to understand the most important concepts related to MQTT. You will learn to make all the necessary configuration to work with digital certificates for encrypting all data sent between the MQTT clients and the server. You will also work with the different Quality of Service levels and later analyze and compare their overheads.
You will write Python 3.x code to control a vehicle with MQTT messages delivered through encrypted connections (TLS 1.2), and learn how leverage your knowledge of the MQTT protocol to build a solution based on requirements. Towards the end, you will write Python code to use the PubNub cloud-based real-time MQTT provider to monitor a surfing competition.
In the end, you will have a solution that was built from scratch by analyzing the requirements and then write Python code that will run on water-proof IoT boards connected to multiple sensors in surfboards.
Python GUI programming with Tkinter
Alan D. Moore
ISBN 13: 9781788835886 Packt 452 Pages (May 2018)
Book Overview:
Find out how to create visually stunning and feature-rich applications by empowering Python's built-in TKinter GUI toolkit
Tkinter is a lightweight, portable, and easy-to-use graphical toolkit available in the Python Standard Library, widely used to build Python GUIs due to its simplicity and availability. This book teaches you to design and build graphical user interfaces that are functional, appealing, and user-friendly using the powerful combination of Python and Tkinter.
After being introduced to Tkinter, you will be guided step-by-step through the application development process. Over the course of the book, your application will evolve from a simple data-entry form to a complex data management and visualization tool while maintaining a clean and robust design. In addition to building the GUI, you'll learn how to connect to external databases and network resources, test your code to avoid errors, and maximize performance using asynchronous programming. You'll make the most of Tkinter's cross-platform availability by learning how to maintain compatibility, mimic platform-native look and feel, and build executables for deployment across popular computing platforms.
By the end of this book, you will have the skills and confidence to design and build powerful high-end GUI applications to solve real-world problems.
Python Penetration Testing Essentials - Second Edition
Mohit
ISBN 13: 9781789138962 Packt 230 Pages (May 2018)
Book Overview:
This book gives you the skills you need to use Python for penetration testing, with the help of detailed code examples. This book has been updated for Python 3.6.3 and Kali Linux 2018.1.
We start by exploring the basics of networking with Python and then proceed to network hacking. Then, you will delve into exploring Python libraries to perform various types of pentesting and ethical hacking techniques. Next, we delve into hacking the application layer, where we start by gathering information from a website. We then move on to concepts related to website hacking—such as parameter tampering, DDoS, XSS, and SQL injection.
By reading this book, you will learn different techniques and methodologies that will familiarize you with Python pentesting techniques, how to protect yourself, and how to create automated programs to find the admin console, SQL injection, and XSS attacks.
Text Processing Using NLTK in Python (Video)
Krishna Bhavsar, Naresh Kumar, Pratap Dangeti
ISBN 13: 9781789348989 Packt Course Length: 1 hour 24 minutes (April 2018)
Video Overview:
Learn the tricks and tips that will help you design Text Analytics solutions
Natural Language Processing (NLP) is a feature of Artificial Intelligence concerned with the interactions between computers and human (natural) languages. This course includes unique videos that will teach you various aspects of performing Natural Language Processing with NLTK—the leading Python platform for the task.
In this course, you will learn what WordNet is and explore its features and usage. It will teach how to extract raw text from web sources and introduce some critical pre-processing steps. You will also get familiarized with the concept of pattern matching as a way to do text analysis.
By the end of the course, you will be confident & have covered various solutions, covering natural language understanding, Natural Language Processing, and syntactic analysis.
Deep Learning with PyTorch (Video)
Anand Saha
ISBN 13: 9781788475266 Packt Course Length: 4 hours 42 minutes (April 2018)
Video Overview:
Build useful and effective deep learning models with the PyTorch Deep Learning framework
In this course, you will learn how to accomplish useful tasks using Convolutional Neural Networks to process spatial data such as images and using Recurrent Neural Networks to process sequential data such as texts. You will explore how you can make use of unlabeled data using Auto Encoders. You will also be training a neural network to learn how to balance a pole all by itself, using Reinforcement Learning. Throughout this journey, you will implement various mechanisms of the PyTorch framework to do these tasks.
By the end of the video course, you will have developed a good understanding of, and feeling for, the algorithms and techniques used. You'll have a good knowledge of how PyTorch works and how you can use it in to solve your daily machine learning problems.
Text Mining with Machine Learning and Python {Video}
Thomas Dehaene
ISBN 13: 9781789137361 Packt Course Length: 2 hours 26 minutes (April 2018)
Video Overview:
Get high-quality information from your text using Machine Learning with Tensorflow, NLTK, Scikit-Learn, and Python
Text is one of the most actively researched and widely spread types of data in the Data Science field today. New advances in machine learning and deep learning techniques now make it possible to build fantastic data products on text sources. New exciting text data sources pop up all the time. You'll build your own toolbox of know-how, packages, and working code snippets so you can perform your own text mining analyses.
You'll start by understanding the fundamentals of modern text mining and move on to some exciting processes involved in it. You'll learn how machine learning is used to extract meaningful information from text and the different processes involved in it. You will learn to read and process text features. Then you'll learn how to extract information from text and work on pre-trained models, while also delving into text classification, and entity extraction and classification. You will explore the process of word embedding by working on Skip-grams, CBOW, and X2Vec with some additional and important text mining processes. By the end of the course, you will have learned and understood the various aspects of text mining with ML and the important processes involved in it, and will have begun your journey as an effective text miner.
Troubleshooting Python Machine Learning {Video}
Rudy Lai
ISBN 13: 9781788999229 Packt Course Length: 3 hours 17 minutes (April 2018)
Video Overview:
Practical and unique solutions to common Machine Learning problems that you face. Avoid any roadblocks while working with the Python data science ecosystem.
You are a data scientist. Every day, you stare at reams of data trying to apply the latest and brightest of models to uncover new insights, but there seems to be an endless supply of obstacles. Your colleagues depend on you to monetize your firm's data - and the clock is ticking. What do you do?
Troubleshooting Python Machine Learning is the answer. We have systematically researched common ML problems documented online around data wrangling, debugging models such as Random Forests and SVMs, and visualizing tricky results. We leverage statistics from Stack Overflow, Medium, and GitHub to get a cross-section of what data scientists struggle with. We have collated for you the top issues, such as retrieving the most important regression features and explaining your results after clustering, and their corresponding solutions. We present these case studies in a problem-solution format, making it very easy for you to incorporate this into your knowledge.
Hussam Khrais
ISBN 13: 9781788838979 Packt 176 Pages (April 2018)
Book Overview:
Your one-stop guide to using Python, creating your own hacking tools, and making the most out of resources available for this programming language
This book is packed with step-by-step instructions and working examples to make you a skilled penetration tester. It is divided into clear bite-sized chunks, so you can learn at your own pace and focus on the areas of most interest to you. This book will teach you how to code a reverse shell and build an anonymous shell. You will also learn how to hack passwords and perform a privilege escalation on Windows with practical examples. You will set up your own virtual hacking environment in VirtualBox, which will help you run multiple operating systems for your testing environment.
By the end of this book, you will have learned how to code your own scripts and mastered ethical hacking from scratch.
Developing NLP Applications Using NLTK in Python (Video)
Krishna Bhavsar, Naresh Kumar, Pratap Dangeti
ISBN 13: 9781789343335 Packt Course Length: 1 hour and 17 minutes ( April 30, 2018 )
Video Overview:
Learn a practical viewpoint to understand and implement NLP solutions involving POS tagging, parsing, and much more
This course is designed with advanced solutions that will take you from newbie to pro in performing Natural Language Processing with NLTK. In this course, you will come across various concepts covering natural language understanding, Natural Language Processing, and syntactic analysis.
It consists of everything you need to efficiently use NLTK to implement text classification, identify parts of speech, tag words, and more. You will also learn how to analyze sentence structures and master syntactic and semantic analysis.By the end of this course, you will have all the knowledge you need to implement Natural Language Processing with Python.
Matplotlib for Python Developers - Second Edition
Aldrin Yim, Claire Chung, Allen Yu
ISBN 13: 9781788625173 Packt 300 Pages (April 2018)
Book Overview:
Leverage the power of Matplotlib to visualize and understand your data more effectively
Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library.
Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book.
Functional Python Programming - Second Edition
Steven F. Lott
ISBN 13: 9781788627061 Packt 408 Pages (April 2018)
Book Overview:
Create succinct and expressive implementations with functional programming in Python
Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds.
You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective.
Jalaj Thanaki
ISBN 13: 9781788390040 Packt 566 Pages (April 2018)
Book Overview:
Practical, hands-on solutions in Python to overcome any problem in Machine Learning
The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, you'll also learn to make more timely and accurate predictions.
In addition, you'll deal with more advanced use cases, such as building a gaming bot, building an extractive summarization tool for medical documents, and you'll also tackle the problems faced while building an ML model. By the end of this book, you'll be able to fine-tune your models as per your needs to deliver maximum productivity.
Mastering Geospatial Analysis with Python
Paul Crickard, Eric van Rees, Silas Toms
ISBN 13: 9781788293334 Packt 440 Pages (April 2018)
Book Overview:
Explore GIS processing and learn to work with various tools and libraries in Python.
Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis.
You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.
Apache Spark with Python - Big Data with PySpark and Spark (Video)
James Lee et al
ISBN 13: 9781789133394 Packt Course Length: 3 hours and 18 minutes (April 2018)
Video Overview:
Learn Apache Spark and Python by 12+ hands-on examples of analyzing big data with PySpark and Spark
This course covers all the fundamentals of Apache Spark with Python and teaches you everything you need to know about developing Spark applications using PySpark, the Python API for Spark. At the end of this course, you will gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adopt Apache Spark for building big data processing pipeline and data analytics applications.
This course covers 10+ hands-on big data examples. You will learn valuable knowledge about how to frame data analysis problems as Spark problems. Together we will learn examples such as aggregating NASA Apache weblogs from different sources; we will explore the price trend by looking at the real estate data in California; we will write Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how makerspaces are distributed across different regions in the United Kingdom. And much much more.
Building Serverless Applications with Python
Jalem Raj Rohit
ISBN 13: 9781787288676 Packt 272 Pages (April 2018)
Book Overview:
Building efficient Python applications at minimal cost by adopting serverless architectures
Serverless architectures allow you to build and run applications and services without having to manage the infrastructure. Many companies have adopted this architecture to save cost and improve scalability. This book will help you design serverless architectures for your applications with AWS and Python.
The book is divided into three modules. The first module explains the fundamentals of serverless architecture and how AWS lambda functions work. In the next module, you will learn to build, release, and deploy your application to production. You will also learn to log and test your application. In the third module, we will take you through advanced topics such as building a serverless API for your application. You will also learn to troubleshoot and monitor your app and master AWS lambda programming concepts with API references. Moving on, you will also learn how to scale up serverless applications and handle distributed serverless systems in production.
All-in-One Introduction to Programming (Video)
Aubrey Love II
ISBN 13: 9781788835206 Packt Course Length: 2 hours 45 minutes (APRIL 2018)
Video Overview:
Five languages in five hours. Get started with programming in HTML5, CSS3, Python, C++, and more!
In this course, you will get to know 5 different languages, compilers, and editors for programming and then you will use HTML5 and CSS3 to build your own company website. As you have successfully stepped into the world of programming, you will now delve into one of the most commonly used Android systems and build an amazing Android application for your company. Next you will master Python and start scripting to build your own Hello World Program. For many people, C++ is just a dream but you will easily master this language and program your Hello World App with C++. Now since you know 5 top languages, you can create a good résumé, create online visibility, and forge ahead in your career. You'll understand several aspects of application development and we guarantee that, by the end of the video, you'll have your very own application up-and-running. For the brave at heart, we also have exercises, at the end of each chapter, which will intrigue you and encourage you to add your own personal touch to the code (and ultimately your application).
Data Visualization Projects in Python (Video)
Harish Garg
ISBN 13: 9781788830416 Packt Course Length: 1 hour 06 minutes (APRIL 2018)
Video Overview:
Data Visualization with bqplot, NetworkX, and Bokeh in Python
You will start by programming stunning interactive Data Visualizations using bqplot, an open source Python library developed by Bloomberg. Then you will learn how to programmatically create interactive network graphs and visualizations. You will then programmatically visualize data with the interactive Python visualization library, Bokeh.
Finally, you will build interactive web visualizations of data using Python: you will choose a number of inputs your users can control, then use any Python graphing library to create plots based on those inputs.
Python for Everyday Life (Video)
Claudio Sparpaglione
ISBN 13: 9781788621953 Packt Course Length: 14 hours 22 minutes (APRIL 2018)
Video Overview:
Make your day and master the Python: a powerful and versatile language and ecosystem that can help you save time and money. This video course is about leveraging the Python programming language and its thriving ecosystem to save yourself time and money when doing common routine tasks. Nobody wants to do boring and time-consuming tasks: days have 24 hours and you should squeeze out the most of this time for yourself - automating the boring tasks gives you back time to focus on what you really like to do. Moreover, this is also the chance for you to learn a great general-purpose language such as Python, with which you can build very cool applications both at work and in your spare time.
The course is structured as an incremental learning path: you will start with a deep-dive into Python software development basics, then move on to write scripts to automate file system operations and file contents processing on your local host, then you will learn how to interact with web-based services such as websites and APIs in order to robotize the cool things that we do everyday - such as tweeting, posting to social networks, reading RSS feeds, etc. - moreover you will practice how to set up a web-based services yourself in the form of web applications and in the end you will learn how to analyze and visualize datasets in order to extract knowledge. By the end of this course you will have learned how to proficiently write structured Python code in a wide range of applications – from one-liner scripts to complex web applications – aiming at the automation of lots of common everyday life tasks.
Machine Learning with scikit-learn and Tensorflow {Video}
Nick Locascio
ISBN 13: 9781788629928 Packt Course Length: 3 hours 58 minutes (MARCH 2018)
Video Overview:
Learn everything you need to know about Machine learning with Tensorflow and Scikit-Learn
Machine Learning is one of the most transformative and impactful technologies of our time. From advertising to healthcare, to self-driving cars, it is hard to find an industry that has not been or is not being revolutionized by machine learning. Using the two most popular frameworks, Tensor Flow and Scikit-Learn, this course will show you insightful tools and techniques for building intelligent systems. Using Scikit-learn you will create a Machine Learning project from scratch, and, use the Tensor Flow library to build and train professional neural networks.
We will use these frameworks to build a variety of applications for problems such as ad ranking and sentiment classification. The course will then take you through the methods for unsupervised learning and what to do when you have limited or no labels for your data. We use the techniques we have learned, along with some new ones, to build a sentiment classifier, an autocomplete keyboard and a topic discoverer.
Hands - On Reinforcement Learning with Python {Video}
Rudy Lai
ISBN 13: 9781788392402 Packt Course Length: 4 hours 28 minutes (MARCH 2018)
Video Overview:
A practical tour of prediction and control in Reinforcement Learning using OpenAI Gym, Python, and TensorFlow
Reinforcement learning (RL) is hot! This branch of machine learning powers AlphaGo and Deepmind's Atari AI. It allows programmers to create software agents that learn to take optimal actions to maximize reward, through trying out different strategies in a given environment.
This course will take you through all the core concepts in Reinforcement Learning, transforming a theoretical subject into tangible Python coding exercises with the help of OpenAI Gym. The videos will first guide you through the gym environment, solving the CartPole-v0 toy robotics problem, before moving on to coding up and solving a multi-armed bandit problem in Python. As the course ramps up, it shows you how to use dynamic programming and TensorFlow-based neural networks to solve GridWorld, another OpenAI Gym challenge. Lastly, we take the Blackjack challenge and deploy model free algorithms that leverage Monte Carlo methods and Temporal Difference (TD, more specifically SARSA) techniques.
Next Generation Natural Language Processing with Python {Video}
Alexis Rutherford
ISBN 13: 9781789139938 Packt Course Length: 1 hour 56 minutes (MARCH 2018)
Video Overview:
Practical techniques and methods to analyze your text data. Power your decision making using next generation libraries.
The company you work for has accumulated a lot of valuable data from its customers, all stored as text, and you need to extract some value from that data. You’ve spent a lot of combined time writing about what they want but no-one knows what they have written about and no-one has the time to read all the messages.
This course empowers you to know how to attack this and other text analysis problems to unlock value for your organization. You’ll start by seeing how NLP can help you extract useful information from large collections of text data, and how you can use the latest Python libraries for NLP. Then we’ll show you how to solve a practical problem using NLP by building a spam SMS detector. You’ll also learn to convert words into numbers that can be analyzed.
Learn Machine Learning in 3 Hours (Video)
Thomas Snell
ISBN 13: 9781788995580 Course Length: 2 hours 14 minutes (March 2018)
Video Overview:
Get hands-on with machine learning using Python
Given the constantly increasing amounts of data they're faced with, programmers have to come up with better solutions to make machines smarter and reduce manual work. In this Machine Learning course, you'll use Python to craft better solutions and process them effectively.
By the end of the course, you will be adept at using the concepts and algorithms involved in Machine Learning. This is a highly practical course and will equip you with sufficient hands-on training to help you implement ML skills right after finishing the course.
Advanced Artificial Intelligence Projects with Python
Joshua Eckroth
ISBN 13: 9781788832403 Packt Course Length: 2 hours 02 minutes (March 2018)
Video Overview:
Enter and explore the fascinating world of intelligent applications with Artificial Intelligence using the Python programming language
Considered the Holy Grail of automation, data analysis, and robotics, Artificial Intelligence has taken the world by storm as a major field of research and development. Python has surfaced as a dominate language in AI/ML programming because of its simplicity and flexibility, in addition to its great support for open source libraries such as spaCy and TensorFlow.
This video course is built for those with a basic understanding of artificial intelligence, introducing them to advanced artificial intelligence projects as they go ahead. The first project introduces natural language processing including part-of-speech tagging and named entity extraction. Wikipedia articles are used to demonstrate the extraction of keywords, and the Enron email archive is mined for mentions and relationships of people, places, and organizations.
Create Your Own Sophisticated Model with Neural Networks (Video)
Julian Avila
ISBN 13: 9781789130157 Packt Course Length: 1 hour and 24 minutes (March 2018)
Video Overview:
AA one-stop solution to learning complex models with Neural Networks and understanding the basics of Natural Language Processing.
With this course you will learn the Decision Tree algorithms and Ensemble Models to build Random Forest, Regression Analysis. You will focus on Decision Trees and Ensemble Algorithms. Moving forward, you learn to use scikit-learn to classify text and Multiclass with scikit-learn. You will explore various algorithms for classification. You will also look at Naive Bayes model and Label Propagation. Finally, you'll use Neural Networks using different Classifiers and create your own Simple Estimator.
Hands-on Artificial Intelligence with TensorFlow (Video)
Saikat Basak
ISBN 13: 9781789135091 Packt Course Length: 1 hour and 36 minutes (March 2018)
Video Overview:
A practical approach to deep learning and deep reinforcement learning for building real-world applications using TensorFlow.
This course will show you how to combine the power of Artificial Intelligence and TensorFlow to develop some exciting applications for the real world. This course will take you through all the relevant AI domains, tools, and algorithms required to build optimal solutions and will show you how to implement them hands-on. You will then be taken through techniques such as reinforcement learning, heuristic searches, neural networks, Computer Vision, OpenAI Gym, and more in different stages of your application. This course will show you how to implement AI practically using TensorFlow models and how it eases the way you interact with the technology.
You will learn how TensorFlow can be used to analyze a variety of data sets and will learn to optimize various AI algorithms. By the end of the course, you will have learned to build intelligent apps by leveraging the full potential of Artificial Intelligence with TensorFlow.
OpenCV 3 Computer Vision with Python Cookbook
Alexey Spizhevoy, Aleksandr Rybnikov
ISBN 13: 9781788474443 Packt 306 Pages (March 2018)
Book Overview:
Recipe-based approach to tackle the most common problems in Computer Vision by leveraging the functionality of OpenCV using Python APIs
In this book, you will learn how to process an image by manipulating pixels and analyze an image using histograms. Then, we'll show you how to apply image filters to enhance image content and exploit the image geometry in order to relay different views of a pictured scene. We’ll explore techniques to achieve camera calibration and perform a multiple-view analysis.
Later, you’ll work on reconstructing a 3D scene from images, converting low-level pixel information to high-level concepts for applications such as object detection and recognition. You’ll also discover how to process video from files or cameras and how to detect and track moving objects. Finally, you'll get acquainted with recent approaches in deep learning and neural networks.
By the end of the book, you’ll be able to apply your skills in OpenCV to create computer vision applications in various domains.
Learning Concurrency in Python (Video)
Elliot Forbes
ISBN 13: 9781789134346 Packt Course Length: 3 hours and 35 minutes (March 2018)
Video Overview:
More than 20 videos to help you master concurrency in Python
This course introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python.
The course will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems. By the end of the video course, you'll have learned techniques to write incredibly efficient concurrent systems that follow best practices.
Hands-On Machine Learning with Python and Scikit-Learn (Video)
Taylor Smith
ISBN 13: 9781788991056 Packt Course Length: 2 hours 39 minutes (March 2018)
Video Overview:
Understand and implement the best Machine Learning practices with the help of powerful features of Python and scikit-learn
This course will help you discover the magical black box that is Machine Learning by teaching a practical approach to modeling using Python along with the Scikit-Learn library.
We begin our journey by observing the end result of a Machine Learning deployment before moving back to the fundamentals and into exploratory data analysis. Moving on, we learn to develop complex pipelines and techniques for building custom transformer objects for feature extraction, manipulation, and other effective data cleansing techniques. Finally, we discover how to select a model, apply optimal hyper-parameters, and deploy it.
Abhinav Dadhich
ISBN 13: 9781788297684 Packt 234 Pages (February 2018)
Book Overview:
A practical guide designed to get you from basics to current state of art in computer vision systems.
In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects.
With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow.
Machine Learning with Scikit-learn (Video)
Gavin Hackeling
ISBN 13: 9781789134780 Packt Course Length: 3 hours 21 minutes (February 2018)
Book OR Video Overview:
Learn to implement and evaluate machine learning solutions with scikit-learn
Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning, you can automate any analytical model. This course examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It also discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more.
You’ll learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance; and develop an intuition for how to improve your model’s performance. By the end of this course, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.
Data Visualization in Python by Examples (Video)
Harish Kumar Garg
ISBN 13: 9781788838658 Packt Course Length: 1 hours 17 minutes (February 2018)
Video Overview:
Data visualization with matplotlib, ggplot, and seaborn in Python
Data visualization is just a wise investment in your future big-data needs. You will learn how to deploy maps and networks to display geographic and network data. To do this, we will focus on the following very popular libraries in Python: matplotlib, ggplot, seaborn, and plotly.
In this course, you will walk through some of the fundamentals of data visualization, sharing many examples of how to handle different types of data and how best to present your insights. We'll take a look at chart types, such as Matplotlib for visualizing the impact of tornadoes in the US, North Korean nuke tests on global stocks, and analyze forex performances using charts. You will see how ggplot can be used to analyze trends in BRICS economies and crude oil price trends. You will see how to level up your data visualization skills using Python's advanced plotting libraries: matplotlib and Seaborn, and how you can present the data from the most unstable regions in the world through data visualization.
Michael Heydt
ISBN 13: 9781787285217 Packt 364 Pages (February 2018)
Book Overview:
Untangle your web scraping complexities and access web data with ease using Python scripts
Right from extracting data from the websites to writing a sophisticated web crawler, the book's independent recipes will be a godsend on the job. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with AJAX websites, paginated items, and more. You will also learn to tackle problems such as 403 errors, working with proxy, scraping images, LXML, and more.
By the end of this book, you will be able to scrape websites more efficiently and to be able to deploy and operate your scraper in the cloud.
Working with Big Data in Python (Video)
Alex Rutherford
ISBN 13: 9781788839068 Course Length: 2 hours 41 minutes (February 2018)
Video Overview:
Gain valuable insights from your data by streamlining unstructured data pipelines with Python, Spark, and MongoDB
This course is a comprehensive, practical guide to using MongoDB and Spark in Python, learning how to store and make sense of huge data sets, and performing basic machine learning tasks to make predictions.
MongoDB is one of the most powerful non-relational database systems available offering robust scalability and expressive operations that, when combined with Python data analysis libraries and distributed computing, represent a valuable set of tools for the modern data scientist. NoSQL databases require a new way of thinking about data and scalable queries. Once Mongo queries have been mastered, it is necessary to understand how we can leverage this API in Python's rich analysis and visualization ecosystem. This course will cover how to use MongoDB, particularly if you are used to SQL databases, with a focus on scalability to large datasets. pyMongo is introduced as the means to interact with a MongoDB database from within Python code and the data structures used to do so are explored. MongoDB uniquely allows for complex operations and aggregations to be run within the query itself and we will cover how to use these operators. While MongoDB itself is built for easy scalability across many nodes as datasets grow, Python is not. Therefore, we cover how we can use Spark with MongoDB to handle more complex machine learning techniques for extremely large datasets. This learning will be applied to several examples of real-world datasets and analyses that can form the basis of your own pipelines, allowing you to quickly get up-and-running with a powerful data science toolkit.
Tomasz Drabas
ISBN 13: 9781788396592 Course Length: 2 hours 29 minutes (February 2018)
Video Overview:
Building and deploying data-intensive applications at scale using Python and Apache Spark
You'll learn about different techniques for collecting data, and distinguish between (and understand) techniques for processing data. Next, we provide an in-depth review of RDDs and contrast them with DataFrames. We provide examples of how to read data from files and from HDFS and how to specify schemas using reflection or programmatically (in the case of DataFrames). The concept of lazy execution is described and we outline various transformations and actions specific to RDDs and DataFrames.
Finally, we show you how to use SQL to interact with DataFrames. By the end of this tutorial, you will have learned how to process data using Spark DataFrames and mastered data collection techniques by distributed data processing.
Concurrent Programming in Python (Video)
BignumWorks Software LLP
ISBN 13: 9781788998031 Course Length: 2 hours 20 minutes (February 2018)
Video Overview:
Harness the power of modern code structures with Python to improve performance and flexibility
Filled with examples, this course will show you all you need to know to start using concurrency in Python. You will learn about the principal approaches to concurrency that Python has to offer, including libraries and tools needed to exploit the performance of your processor. Learn the basic theory and history of parallelism and choose the best approach when it comes to parallel processing.
After taking this course you will have gained an in-depth knowledge of using threads and processes with the help of real-world examples.
Concurrent Programming in Python (Video)
BignumWorks Software LLP
ISBN 13: 9781788998031 Course Length: 2 hours 20 minutes (February 2018)
Video Overview:
Harness the power of modern code structures with Python to improve performance and flexibility
Filled with examples, this course will show you all you need to know to start using concurrency in Python. You will learn about the principal approaches to concurrency that Python has to offer, including libraries and tools needed to exploit the performance of your processor. Learn the basic theory and history of parallelism and choose the best approach when it comes to parallel processing.
After taking this course you will have gained an in-depth knowledge of using threads and processes with the help of real-world examples.
Vishnu Subramanian
ISBN 13: 9781788624336 Packt 262 Pages (February 2018)
Book Overview:
Build neural network models in text, vision and advanced analytics using PyTorch
This book will get you up and running with one of the most cutting-edge deep learning libraries—PyTorch. PyTorch is grabbing the attention of deep learning researchers and data science professionals due to its accessibility, efficiency and being more native to Python way of development. You'll start off by installing PyTorch, then quickly move on to learn various fundamental blocks that power modern deep learning. You will also learn how to use CNN, RNN, LSTM and other networks to solve real-world problems. This book explains the concepts of various state-of-the-art deep learning architectures, such as ResNet, DenseNet, Inception, and Seq2Seq, without diving deep into the math behind them.
You will also learn about GPU computing during the course of the book. You will see how to train a model with PyTorch and dive into complex neural networks such as generative networks for producing text and images.By the end of the book, you'll be able to implement deep learning applications in PyTorch with ease.
Python Network Programming (Video)
Eric Chou
ISBN 13: 9781788479387 Course Length: 2 hours and 3 minutes (February 2018)
Video Overview:
Accomplish Network Engineering Tasks with Python
You will learn to create exciting Python apps to automate daily networking tasks such as configuring devices, collecting information about the network, testing by client simulations, or network discovery. This course will help you build some mesmerizing network tools with Python, including a Subnet calculator; configuring multiple network devices concurrently via SSH or Telnet; a DHCP client simulator for testing a DHCP server in the local network; network discovery via SNMP; OS fingerprinting; and network attacks via Scapy. This tutorial uses real-life scenarios and use cases to help you build network automation tools with the amazing Python language. By the end of this course, you will be able to take your Python programming skills to the next level for network automation.
This course provides hands-on, interesting examples with clear and friendly explanations that students can follow along with, covers common mistakes, and provides useful tips and in-the-trenches advice. There is a limited amount of theory; instead, the examples are full of real-world use cases.
Daniel Furtado, Marcus Pennington
ISBN 13: 9781786468161 Packt 456 Pages (February 2018)
Book Overview:
How to build useful, real-world applications in the Python programming language
In this book, we will cover some of the most common tasks that Python developers face on a daily basis, including performance optimization and making web applications more secure. We will familiarize ourselves with the associated software stack and master asynchronous features in Python. We will build a weather application using command-line parsing. We will then move on to create a Spotify remote control where we'll use OAuth and the Spotify Web API. The next project will cover reactive extensions by teaching you how to cast votes on Twitter the Python way. We will also focus on web development by using the famous Django framework to create an online game store. We will then create a web-based messenger using the new Nameko microservice framework.
We will cover topics like authenticating users and, storing messages in Redis. By the end of the book, you will have gained hands-on experience in coding with Python.
Building Advanced OpenCV3 Projects with Python (Video)
Riaz Munshi
ISBN 13: 9781788394291 Packt Course Length: 3 hours 30 minutes (January 2018)
Video Overview:
Discover how to build advanced OpenCV3 projects with Python
This course features some trending applications of vision and deep learning and will help you master these techniques. You will learn how to retrieve structure from motion (sfm) and you will also see how we can build an application to capture 2D images and join them dynamically to achieve street views by capturing camera projection angles and relative image positions. You will also learn how to track your head in 3D in real-time, and perform facial recognition against a goldenset. You will also build an app to capture facial emotions based on a CovNet.
Next, you'll generate panoramas using image stitching and we extend this concept by generating a map based on the trajectory of ISS. You'll also learn to build an application to capture beautiful panoramas and also achieve AR effects. You then delve into one of the most trending domains of computer vision: autonomous cars. You'll learn about various architectures and develop the skills to detect lanes, and segment and track vehicles in traffic.You will be using Carla, which is a open driving simulator by Intel, for your project to train a car learn how to drive itself using an end-to-end model.
Wei Di, Anurag Bhardwaj, Jianing Wei
ISBN 13: 9781785880360 Packt 284 Pages (Jan 2018)
Book Overview:
Get to grips with the essentials of deep learning by leveraging the power of Python
This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more
This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications
Training Your Systems with Python Statistical Modeling (Video)
Curtis Miller
ISBN 13: 9781788293402 Packt Course Length: 4 hours 5 minutes (Jan 2018)
Video Overview:
Learn statistical analysis by using various machine learning models
You’ll start by diving into classical statistical analysis, where you will learn to compute descriptive statistics with Pandas. From there, you will be introduced to supervised learning, where you will explore the principles of machine learning and train different machine learning models. Next, you’ll work with binary prediction models, such as data classification using K-nearest neighbors, decision trees, and random forests.
After that, you’ll work with algorithms for regression analysis, and employ different types of regression, such as ridge and lasso regression, and spline interpolation using SciPy. Then, you’ll work on neural networks, train them, and employ regression on neural networks. You’ll be introduced to clustering, and learn to evaluate cluster model results, as well as employ different clustering types such as hierarchical and spectral clustering. Finally, you’ll learn about the dimensionality reduction concepts such as principal component analysis and low dimension representation.
Effective Prediction with Machine Learning - Second Edition (Video)
Julian Avila
ISBN 13: 9781789132793 Packt Course Length: 1 hour 32 minutes (Jan 2018)
Video Overview:
A one-stop solution to quickly program fast Machine Learning algorithms with NumPy and scikit-learn
This course begins by taking you through videos on evaluating the statistical properties of data and generating synthetic data for machine learning modeling. As you progress through the sections, you will come across videos that will teach you to implement techniques such as data pre-processing, linear regression, logistic regression, and K-NN. You will also look at Pre-Model and Pre-Processing workflows, to help you choose the right models.
Finally, you'll explore dimensionality reduction with various parameters.
IPython Interactive Computing and Visualization Cookbook - Second Edition
Cyrille Rossant
ISBN 13: 9781785888632 Packt 548 Pages (Jan 2018)
Book Overview:
Learn to use IPython and Jupyter Notebook for your data analysis and visualization work.
IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning.
The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.
Ankit Dixit
ISBN 13: 9781788297752 Packt 438 Pages (December 2017)
Book Overview:
An effective guide to using ensemble techniques to enhance machine learning models
This book covers different machine learning algorithms that are widely used in the practical world to make predictions and classifications. It addresses different aspects of a prediction framework, such as data pre-processing, model training, validation of the model, and more. You will gain knowledge of different machine learning aspects such as bagging (decision trees and random forests), Boosting (Ada-boost) and stacking (a combination of bagging and boosting algorithms).
Then you’ll learn how to implement them by building ensemble models using TensorFlow and Python libraries such as scikit-learn and NumPy. As machine learning touches almost every field of the digital world, you’ll see how these algorithms can be used in different applications such as computer vision, speech recognition, making recommendations, grouping and document classification, fitting regression on data, and more.
Connect the Dots: Factor Analysis (Video)
Loonycorn
ISBN 13: 9781788997522 Packt Course Length: 1 hour 43 minutes (December 2017)
Video Overview:
Factor extraction using PCA in Excel, R and Python
Factor analysis helps to cut through the clutter when you have a lot of correlated variables to explain a single effect. This course will help you understand Factor analysis and it’s link to linear regression.
See how Principal Components Analysis is a cookie cutter technique to solve factor extraction and how it relates to Machine learning.
Connect the Dots: Linear and Logistic Regression (Video)
Loonycorn
ISBN 13: 9781788991957 Packt Course Length: 4 hours 45 minutes (December 2017)
Video Overview:
Build robust models in Excel, R and Python
This course will teach you how to build robust linear models and do logistic regression in Excel, R and Python. Let’s parse that. Robust linear models: Linear Regression is a powerful method for quantifying the cause and effect relationships that affect different phenomena in the world around us.
This course will teach you how to build robust linear models that will stand up to scrutiny when you apply them to real world situations. Logistic regression: Logistic regression has many cool applications: analyzing consequences of past events, allocating resources, solving binary classification problems using machine learning and so on. This course will help you understand the intuition behind logistic regression and how to solve it using cookie-cutter techniques. Excel, R and Python: Put what you've learnt into practice. Leverage these powerful analytical tools to build models for stock returns.
Advanced Statistics for Machine Learning (Video)
Pratap Dangeti
ISBN 13: 9781788994989 Packt Course Length: 2 hours 10 minutes (December 2017)
Video Overview:
Building various machine learning models using Python and R
This video will teach you all it takes to perform the complex statistical computations required for Machine Learning. You will gain information on statistics behind unsupervised learning, reinforcement learning, and more. You'll master real-world examples that discuss the statistical side of Machine Learning.
In this video, you will acquire a deep knowledge of the various models of unsupervised and reinforcement learning, and explore the fundamentals of deep learning with the help of the Keras software. Furthermore, you'll gain an overview of reinforcement learning with the Python programming language.
Natural Language Processing with Python (Video)
Tyler Edwards
ISBN 13: 9781787286085 Packt Course Length: 1 hour 47 minutes (December 2017)
Video Overview:
Learn and master the NLTK library in Python to create your own NLP apps
You will start off by preparing text for Natural Language Processing by cleaning and simplifying it. Then you will implement more complex algorithms to break this text down and uncover contextual relationships that reveal the meaning and content of the text. You will learn how to tokenize various parts of sentences, and how to analyze them. You will learn about semantic as well as the syntactic analysis of text.
During this course, you will learn how to solve various ambiguities in processing human language. You will also gain experience with NLP using Python and will be introduced to a variety of useful tools in NLTK. Plus, you will have an opportunity to build your first NLP application. By the end of this course, you will have the skills and tools to begin solving problems in the growing field of Latent Semantic Analysis.
Python: Advanced Predictive Analytics
Ashish Kumar, Joseph Babcock
ISBN 13: 9781788992367 Packt 660 Pages (December 2017)
Book Overview:
Gain practical insights by exploiting data in your business to build advanced predictive modeling applications
This book is your guide to getting started with predictive analytics using Python. You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications.
Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates explains how these methods work. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring to life the insights of predictive modeling.
Practical Time Series Analysis (Video)
Dr. Avishek Pal, Dr. PKS Prakash
ISBN 13: 9781788995719 Packt Course Length: 2 hours 25 minutes (December 2017)
Video Overview:
Step-by-step guide filled with real-world practical examples
The video starts with a descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality, and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, we shift the focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting.
Later, powerful deep learning methods are presented to develop accurate forecasting models for complex time series. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python.
L. Felipe Martins, Ruben Oliva Ramos, V Kishore Ayyadevara
ISBN 13: 9781788291460 Packt 386 Pages (December 2017)
Book Overview:
Tackle the most sophisticated problems associated with scientific computing and data manipulation using SciPy
This book includes hands-on recipes for using the different components of the SciPy Stack such as NumPy, SciPy, matplotlib, and pandas, among others. You will use these libraries to solve real-world problems in linear algebra, numerical analysis, data visualization, and much more. The recipes included in the book will ensure you get a practical understanding not only of how a particular feature in SciPy Stack works, but also of its application to real-world problems.
The independent nature of the recipes also ensure that you can pick up any one and learn about a particular feature of SciPy without reading through the other recipes, thus making the book a very handy and useful guide.
Advanced Techniques for Exploring Data Sets with Pandas (Video)
Harish Garg
ISBN 13: 9781788397599 Packt Course Length: 1 hours 45 minutes (July 2017)
Video Overview:
Explore popular datasets in R, while mastering advanced techniques used for them
In this course, you will learn how to start using pandas from end-to-end: from getting your data into pandas; using pandas to manipulate, transform, analyze, and visualize data; to ultimately taking your transformed data out of pandas into any number of formats.
scikit-learn : Machine Learning Simplified
Raúl Garreta, Guillermo Moncecchi, Trent Hauck, Gavin Hackeling
ISBN 13: 9781788833479 Packt 530 Pages (November 2017)
Book Overview:
Implement scikit-learn into every step of the data science pipeline
The course combines an introduction to some of the main concepts and methods in machine learning with practical, hands-on examples of real-world problems. The course starts by walking through different methods to prepare your data—be it a dataset with missing values or text columns that require the categories to be turned into indicator variables. After the data is ready, you'll learn different techniques aligned with different objectives—be it a dataset with known outcomes such as sales by state, or more complicated problems such as clustering similar customers. Finally, you'll learn how to polish your algorithm to ensure that it's both accurate and resilient to new datasets.
Natural Language Processing with Python Cookbook
Krishna Bhavsar, Naresh Kumar, Pratap Dangeti
ISBN 13: 9781787289321 Packt 294 Pages (November 2017)
Book Overview:
Learn the tricks and tips that will help you design Text Analytics solutions
This book includes unique recipes that will teach you various aspects of performing Natural Language Processing with NLTK—the leading Python platform for the task. You will come across various recipes during the course, covering (among other topics) natural language understanding, Natural Language Processing, and syntactic analysis. You will learn how to understand language, plan sentences, and work around various ambiguities. You will learn how to efficiently use NLTK and implement text classification, identify parts of speech, tag words, and more. You will also learn how to analyze sentence structures and master lexical analysis, syntactic and semantic analysis, pragmatic analysis, and the application of deep learning techniques.
By the end of this book, you will have all the knowledge you need to implement Natural Language Processing with Python.
Advanced Predictive Techniques with Scikit-Learn and TensorFlow (Video)
Alvaro Fuentes
ISBN 13: 9781788295321 Packt Course Length: 3 hours 44 minutes (November 2017)
Video Overview:
Improve the performance predictive models, build more complex models and use techniques to improve quality of your predictive models.
Ensemble methods offer a powerful way to improve prediction accuracy by combining in a clever way predictions from many individual predictors. In this course, you will learn how to use ensemble methods to improve accuracy in classification and regression problems.
When using Predictive Analytics to solve actual problems, besides models and algorithms there are many other practical considerations that must be considered like which features should you use, how many features are enough, should you create new features, how to combine features to give the same underlying information, which hyper-parameters should you use? You explore topics that will help you answer such questions.
Artificial Neural Networks are models loosely based on how neural networks work in a living being. These models have a long history in the Artificial Intelligence community with ups and downs in popularity. Nowadays, because of the increase in computational power, improved methods, and software enhancements, they are popular again and are the basis for advanced approaches such as Deep Learning. This course introduces the use of Deep Learning models for Predictive Analytics using the powerful TensorFlow library.
Cryptography with Python (Video)
Sam Bowne
ISBN 13: 9781788397179 Packt Course Length: 1 hours 30 minutes (November 2017)
Video Overview:
Encrypt, evaluate, compare, and attack your data
Cryptography is essential to protect sensitive information, but it is often performed inadequately or incorrectly. Learn how to encrypt data, evaluate and compare encryption methods, and how to attack them. This video course starts by showing you how to encrypt and evaluate your data. You are also walked through various data encryption methods—such as obfuscation, hashing, and strong encryption—and how you can attack them. You will then learn how to make hashes and crack them, and understand why they are so different. You will also learn how to use three NIST-recommended systems: AES, SHA, and RSA. Towards the end of the course, you will master common errors in encryption and how to exploit them.
The goal of this course is to show viewers how to encrypt data, evaluate and compare encryption methods, and attack them.
Julien Danjou
ISBN: 978-1-387-37932-3 – 300 pages – (December 2017)
Book Overview:
Python is a wonderful programming language that allows to write applications quickly. But how do you make those applications scale for thousands of users and requests? It takes years of practice, research, trial and errors to build experience and knowledge along the way. Simple questions such as "How do I make my code faster?" or "How do I make sure there is no bottleneck?" cost hours to find good answers. Without enough background on the topic, you'll never be sure that any answer you'll come up with will be correct. The Hacker's Guide to Scaling Python will help you solve that by providing guidelines, tips and best practice. Adding a few interview of experts on the subject, you will learn how you can distribute your Python application so it is able to process thousands of requests.
Matplotlib for Python Developers (Video)
Benjamin Keller
ISBN 13: 9781787281998 Packt Publishing Course Length: 2 hours 56 minutes (October 2017)
Video Overview:
Understand the basic fundamentals of plotting and data visualization using Matplotlib
In this course, you hit the ground running and quickly learn how to make beautiful, illuminating figures with Matplotlib and a handful of other Python tools. You understand data dimensionality and set up an environment by beginning with basic plots. You enter into the exciting world of data visualization and plotting. You'll work with line and scatter plots and construct bar plots and histograms. You'll also explore images, contours, and histograms in depth. Plot scaffolding is a very interesting topic wherein you'll be taken through axes and figures to help you design excellent plots. You'll learn how to control axes and ticks, and change fonts and colors. You'll work on backends and transformations. Then lastly you'll explore the most important companions for Matplotlib, Pandas and Jupyter, used widely for data manipulation, analysis, and visualization.
By the end of this course you'll be able to construct effective and beautiful data plots using the Matplotlib library for the Python programming language.
Python GUI Programming Recipes using PyQt5 (Video)
Burkhard Meier
ISBN 13: 9781788471268 Packt Publishing Course Length: 4 hours 09 minutes (October 2017)
Video Overview:
Learn to design a UI with help of PyQT5
In this video, you will successfully install PyQt5 and the toolset that contains the QT Designer tool. The QT Designer enables you to develop our GUI in a visual manner, using drag and drop to add and position widgets, and we will use it extensively. We will then learn how to convert QT Designer-generated code into pure Python code.
After having successfully installed PyQt5, the QT Designer, and all other required QT tools, you will start out simple, building a Python GUI using only a few lines of PyQT5 code. Then, you will build a more complex GUI using QT Designer. Along the way, you will explore many QT widgets and learn how to efficiently lay out our GUI design. You will enhance the look-and-feel of the GUI using CSS styling. You will also connect our GUI to a SQL database, which we will create. You decouple the business logic code from the UI code, using best practices. At the end of this video tutorial, viewers will be able to develop complex GUIs using PyQt5.
Python Design Patterns (Video)
Tong Qiu
ISBN 13: 9781786460677 Packt Publishing Course Length: 2 hours 26 minutes (September 2017)
Video Overview:
Design patterns to improve the speed, code reuse, and performance of your Python applications.
This course focuses on showing you the practical aspects of smarter coding in Python.
Get into the world of design patterns and brush up on your OOP skills. Explore the most widely used patterns and create objects in a manner best suited to the situation. Some patterns will help you identify simple ways to realize relationships between entities. Next, learn how to encapsulate behaviour in an object and delegate requests to it, before delving into some advanced patterns. With this course, you will be well equipped to craft faster, cleaner, and smarter applications.
Mastering Python Data Analysis with Pandas (Video)
Prabhat Ranjan
ISBN 13: 9781787280083 Packt Publishing Course Length: 1 hour 17 minutes (September 2017)
Video Overview:
Learn how to use Pandas, the Python library for data and statistical analysis.
This course is your guide to implementing the more advanced offerings of the popular Pandas library and explains how it can solve real-world problems. After a brief overview of the basics—such as data structures and various data manipulation tasks such as grouping, merging, and reshaping data—this video also teaches you how to manipulate, analyse, and visualize your time-series financial data.
You will learn how to apply Pandas to important but simple financial tasks such as modelling portfolios, calculating optimal portfolios based upon risk, and more. This video not only teaches you why Pandas is a great tool for solving real-world problems in quantitative finance, it also takes you meticulously through every step of the way, with practical, real-world examples, especially from the financial domain where Pandas is a popular choice. By the end of this video, you will be an expert in using the Pandas library for any data analysis problem, especially related to finance.
Architectural Patterns and Best Practices with Python (Video)
Anand Balachandran Pillai
ISBN 13: 9781788838276 Packt Publishing Course Length: 1 hour 37 minutes (September 2017)
Video Overview:
Implement various Architectural patterns and learn to deploy and debug your Python applications.
This video starts off by explaining how Python fits into application architecture. As you move along, you will understand the architecturally significant demands and how to determine them. Later, you’ll get a complete understanding of the different architectural patterns such as event driven programming, microservice architecture and pipe and filter architecture. Python, as an open-source language, has matured in the level of automation and support it provides for deploying packages to production systems. Get to understand deployment of Python applications, and the tools and processes that the architect can add to his repertoire in order to ease the deploying and maintenance of his production systems' running applications, written using Python.
Python 3.x for Computer Vision (Video)
Saurabh Kapur
ISBN 13: 9781788838207 Packt Publishing Course Length: 1 hour 29 minutes (September 2017)
Video Overview:
Unleash the power of computer vision with Python to carry out image processing and computer vision techniques.
This video course is a practical guide for developers who want to get started with building computer vision applications using Python 3. Throughout this video course, three image processing libraries: Pillow, Scikit-Image, and OpenCV are used to implement different computer vision algorithms.
The course will help you build Computer Vision applications that are capable of working in real-world scenarios effectively. Some of the applications that we look at in the course are Optical Character Recognition, Object Tracking and building a Computer Vision as a Service platform that works over the internet.
Data Acquisition and Manipulation with Python (Video)
Curtis Miller
ISBN 13: 9781788291415 Packt Publishing Course Length: 2 hours 39 minutes (September 2017)
Video Overview:
Acquire and analyse data in different formats with the help of Python data analysis tools.
In this course, you’ll start by learning how to acquire data from the web in its already “clean” format, such as in a .csv file, or a database. You’ll then learn to transform this data so it’s in its most useful format for analysis. After that, you’ll dive into data aggregation and grouping, where you’ll learn to group similar data for easier analysis purposes. From there, you’ll be shown different methods of web scraping using Python. Finally, you’ll learn to extract large amounts of data using BeautifulSoup, as well as work with Selenium and Scrapy.
Python For Android Hacking Crash Course: Trojan Perspective (Video)
Hussam Khrais
ISBN 13: 9781788626255 Packt Publishing Course Length: 3 hours 16 minutes (September 2017)
Video Overview:
Acquire and analyse data in different formats with the help of Python data analysis tools.
This friendly course takes you through Python For Android Hacking Crash Course. It is packed with step-by-step instructions and working examples. This comprehensive course is divided into clear bite-size chunks so you can learn at your own pace and focus on the areas of most interest to you.
Python For Offensive PenTest: A Complete Practical Course (Video)
Hussam Khrais
ISBN 13: 9781788628068 Packt Publishing Course Length: 5 hours 57 minutes (September 2017)
Video Overview:
Python for Hacking , Learn how to use python for ethical hacking and penetration testing.
Firstly, download the script, read the inline comments, run the script in your home lab, then finally see the explanatory video. Learn how to code your own reverse shell [TCP+HTTP]. Make anonymous shell by interacting with [Twitter, Google Form, Sourceforge]. Replicate Metasploit features and make an advanced shell and much more.
Python Machine Learning - Second Edition
Sebastian Raschka, Vahid Mirjalili
ISBN 13: 9781787125933 Packt Publishing 622 pages (September 2017)
Book Overview:
Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries
Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschka’s bestselling book, Python Machine Learning. Thoroughly updated using the latest Python open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis.
Fully extended and modernized, Python Machine Learning Second Edition now includes the popular TensorFlow deep learning library. The scikit-learn code has also been fully updated to include recent improvements and additions to this versatile machine learning library.
Practical Python Data Science Techniques (Video)
Marco Bonzanini
ISBN 13: 9781788294294 Packt Publishing Course Length: 2 hours 32 minutes (August 2017)
Video Overview:
Learn practical solutions to Data Science problems with Python
A comprehensive course packed with step-by-step instructions, working examples, and helpful advice on Data Science Techniques in Python. This comprehensive course is divided into clear bite size chunks so you can learn at your own pace and focus on the areas that interest you the most.
Making Predictions with Data and Python (Video)
Alvaro Fuentes
ISBN 13: 9781788297448 Packt Publishing Course Length: 4 hours 10 minutes (August 2017)
Video Overview:
Build Awesome Predictive Models with Python
This course introduces the main concepts, techniques, and best practices for doing Predictive Analytics with Python. Using an example-based approach, it covers all the stages in the process of building predictive models with Python. By the end of the course you will be able to build Predictive Analytics models using real-world data.
Python Network Programming Cookbook - Second Edition
Pradeeban Kathiravelu, Dr. M. O. Faruque Sarker
ISBN 13: 9781786463999 Packt Publishing 450 pages (August 2017)
Book Overview:
Discover practical solutions for a wide range of real-world network programming tasks
Python Network Programming Cookbook - Second Edition highlights the major aspects of network programming in Python, starting from writing simple networking clients to developing and deploying complex Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) systems.
In this edition, you will also be introduced to network modelling to build your own cloud network. You will learn about the concepts and fundamentals of SDN and then extend your network with Mininet. Next, you’ll find recipes on Authentication, Authorization, and Accounting (AAA) and open and proprietary SDN approaches and frameworks.
Functional Programming in Python (Video)
Sebastiaan Mathôt
ISBN 13: 9781788292450 Packt Publishing Course Length: 2 hours and 34 minutes (July 2017)
Video Overview:
In this video course, you will learn what functional programming is, and how it differs from other programming styles, such as procedural and object-oriented programming. You will also learn why and when functional programming is useful, and why and when it makes programs unnecessarily complex. Explore lambda expressions, which are short one-line functions, and are the purest form of functional programming that Python offers. Next, learn about higher-order functions: functions that accept other functions as argument, or return other functions as return values. In Python, higher-order functions are elegantly supported through decorators. You will also encounter important concepts from functional programming, such as monads, currying, statelessness, side-effects, memoization, and referential transparency; these concepts may initially seem odd to Python programmers, but you will see how they are elegantly supported by the language. In fact, many Python programmers already make use of concepts from functional programming without being aware of doing so.
All the videos in this course contain hands-on examples of the introduced concepts.
What you will learn:
- Recognize the value of Functional Programming
- Understand the advantages and disadvantages of Functional Programming
- Higher-order functions and Lambda expressions (nameless functions)
- Error handling in Functional Programming
- Understand common functional design patterns, and how these apply to Python
Mastering Machine Learning with scikit-learn - Second Edition
Gavin Hackeling
ISBN 13: 9781788299879 Packt Publishing 254 pages (July 2017)
Book Overview:
This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance.
By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.
What you will learn:
- Review fundamental concepts such as bias and variance
- Extract features from categorical variables, text, and images
- Predict the values of continuous variables using linear regression and K Nearest Neighbors
- Classify documents and images using logistic regression and support vector machines
- Create ensembles of estimators using bagging and boosting techniques
- Discover hidden structures in data using K-Means clustering
- Evaluate the performance of machine learning systems in common tasks
Python Natural Language Processing
Jalaj Thanaki
ISBN 13: 9781787121423 Packt Publishing 486 pages (July 2017)
Book Overview:
This book starts off by laying the foundation for Natural Language Processing and why Python is one of the best options to build an NLP-based expert system with advantages such as Community support, availability of frameworks and so on. Later it gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them.
What you will learn:
- Focus on Python programming paradigms, which are used to develop NLP applications
- Understand corpus analysis and different types of data attribute
Learn NLP using Python libraries such as NLTK, Polyglot, SpaCy, Standford CoreNLP and so on
- Learn about Features Extraction and Feature selection as part of Features Engineering
- Explore the advantages of vectorization in Deep Learning
- Get a better understanding of the architecture of a rule-based system
- Optimize and fine-tune Supervised and Unsupervised Machine Learning algorithms for NLP problems
- Identify Deep Learning techniques for Natural Language Processing and Natural Language Generation problems
Manish Sethi
ISBN 13: 9781787129313 Packt Publishing 374 pages (July 2017)
Book Overview:
This book will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you’ll learn how to build microservices in Python using REST APIs in an event driven approach and you will build the web layer. Next, you’ll learn about Interacting data services and building Web views with React, after which we will take a detailed look at application security and performance. Then, you’ll also learn how to Dockerize your services. And finally, you’ll learn how to deploy the application on the AWS and Azure platforms.
This book will teach you how to craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: we're going to build everything using Python 3 and its amazing tooling ecosystem. The book will take you on a journey, the destination of which, is the creation of a complete Python application based on microservices over the cloud platform.
What you will learn:
- Get to know “the way of the cloud”, including why developing good cloud software is fundamentally about mindset and discipline
- Know what microservices are and how to design them
- Create reactive applications in the cloud with third-party messaging providers
- Build massive-scale, user-friendly GUIs with React and Flux
- Secure cloud-based web applications: the do’s, don’ts, and options
- Plan cloud apps that support continuous delivery and deployment
Siddhartha Chatterjee, Michal Krystyanczuk
ISBN 13: 9781787121485 Packt Publishing 312 pages (July 2017)
Book Overview:
Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup.
Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes.
What you will learn:
- Understand the basics of social media mining
Use PyMongo to clean, store, and access data in MongoDB
- Understand user reactions and emotion detection on Facebook
- Perform Twitter sentiment analysis and entity recognition using Python
Analyze video and campaign performance on YouTube
Mine popular trends on GitHub and predict the next big technology
- Extract conversational topics on public internet forums
- Analyze user interests on Pinterest
- Perform large-scale social media analytics on the cloud
Python Microservices Development
Tarek Ziadé
ISBN 13: 9781785881114 Packt Publishing 340 pages (July 2017)
Book Overview:
An efficient way to build applications to do this is through microservices architecture. But, in practice, it's hard to get this right due to the complexity of all the pieces interacting with each other.
This book will teach you how to overcome these issues and craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: you’ll build everything using Python 3 and its amazing tooling ecosystem. You will understand the principles of TDD and apply them.
This book will take you on a journey, ending with the creation of a complete Python application based on microservices. By the end of the book, you will be well versed with the fundamentals of building, designing, testing, and deploying your Python microservices.
What you will learn:
- Explore what microservices are and how to design them
- Use Python 3, Flask, Tox, and other tools to build your services using best practices
- Learn how to use a TDD approach
- Discover how to document your microservices
- Configure and package your code in the best way
- Interact with other services
- Secure, monitor, and scale your services
- Deploy your services in Docker containers, CoreOS, and Amazon Web Services
Eric Chou
ISBN 13: 9781784397005 Packt Publishing 446 pages (June 2017)
Book Overview:
This book begins with a review of the TCP/ IP protocol suite and a refresher of the core elements of the Python language. Next, you will start using Python and supported libraries to automate network tasks from the current major network vendors. You will look at automating traditional network devices based on the command-line interface, as well as newer devices with API support, with hands-on labs. You will then learn the concepts and practical use cases of the Ansible framework in order to achieve your network goals.
You will then move on to using Python for DevOps, starting with using open source tools to test, secure, and analyze your network. Then, you will focus on network monitoring and visualization. You will learn how to retrieve network information using a polling mechanism, flow-based monitoring, and visualizing the data programmatically. Next, you will learn how to use the Python framework to build your own customized network web services.
In the last module, you will use Python for SDN, where you will use a Python-based controller with OpenFlow in a hands-on lab to learn its concepts and applications. Compare and contrast OpenFlow, OpenStack, OpenDaylight, and NFV. Finally, you will use everything you’ve learned in the book to construct a migration plan to go from a legacy to a scalable SDN-based network.
What you will learn:
- Review all the fundamentals of Python and the TCP/IP suite
- Use Python to execute commands when the device does not support the API or programmatic interaction with the device
- Implement automation techniques by integrating Python with Cisco, Juniper, and Arista eAPI
- Integrate Ansible using Python to control Cisco, Juniper, and Arista networks
- Achieve network security with Python
- Build Flask-based web-service APIs with Python
- Construct a Python-based migration plan from a legacy to scalable SDN-based network
Practical Data Science Cookbook - Second Edition
Prabhanjan Tattar, Tony Ojeda, Sean Patrick Murphy, Benjamin Bengfort, Abhijit Dasgupta
ISBN 13: 9781787129627 Packt Publishing 434 pages (June 2017)
Book Overview:
Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python.
What you will learn:
- Learn and understand the installation procedure and environment required for R and Python on various platforms
- Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python
- Build a predictive model and an exploratory model
- Analyze the results of your model and create reports on the acquired data
- Build various tree-based methods and Build random forest
Unpacking NumPy and Pandas (Video)
Curtis Miller
ISBN 13: 9781787121195 Packt Publishing Course Length: 2 hours and 18 minutes (June 2017)
Video Overview:
In this video course, you will explore two of the most important Python packages used by Data Analysts. You will start off by learning how to set up the right environment for data analysis with Python. Here, you’ll learn to install the right Python distribution, as well as work with the Jupyter notebook, and set up a database. After that you will dive into Python’s NumPy package, Python’s powerful extension with advanced mathematical functions. You will learn to create NumPy arrays, as well as employ different array methods and functions. Then, you will explore Python’s Pandas extension, where you will learn to subset your data, as well as dive into data mapping using Pandas. You’ll also learn to manage your data sets by sorting and ranking them. Finally, you will learn to index and group your data for sophisticated data analysis and manipulation.
What you will learn:
How to read, sort, and map various data into NumPy and Pandas
How to create and slice data arrays using NumPy
- How to subset your data frames using Pandas
How to handle missing data in a Pandas DataFrame
- How to interface your Python data analysis with R language packages
Python for Finance - Second Edition
Yuxing Yan
ISBN 13: 9781787125698 Packt Publishing 586 pages (June 2017)
Book Overview:
This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance.
The book starts by explaining topics exclusively related to Python. Then deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures.
What you will learn:
- Become acquainted with Python in the first two chapters
- Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models
- Learn how to price a call, put, and several exotic options
- Understand Monte Carlo simulation, how to write a Python program to replicate the Black-Scholes-Merton options model, and how to price a few exotic options
- Understand the concept of volatility and how to test the hypothesis that volatility changes over the years
- Understand the ARCH and GARCH processes and how to write related Python programs
Python Web Scraping - Second Edition
Katharine Jarmul, Richard Lawson
ISBN 13: 9781786462589 Packt Publishing 220 pages (May 2017)
Book Overview:
This book is the ultimate guide to using the latest features of Python 3.x to scrape data from websites. In the early chapters, you’ll see how to extract data from static web pages. You’ll learn to use caching with databases and fil
Natural Language Processing Fundamentals
Sohom Ghosh, Dwight Gunning
ISBN 13: 9781789954043 Packt 374 Pages (March 2019)
Book Overview:
Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems.
If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems.
You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals.The book will easily equip you with the knowledge you need to build applications that interpret human language.
Deep Learning with PyTorch Quick Start Guide
David Julian
ISBN 13: 9781789534092 Packt 118 pages (December 2018)
Book Overview:
PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power.
This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text.
By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease.
Hyatt Saleh
ISBN 13: 9781789803556 Packt 240 Pages (November 2018)
Book Overview:
With the flexibility and features of scikit-learn and Python, build machine learning algorithms that optimize the programming process and take application performance to a whole new level
As machine learning algorithms become popular, new tools that optimize these algorithms are also developed. Machine Learning Fundamentals explains you how to use the syntax of scikit-learn. You'll study the difference between supervised and unsupervised models, as well as the importance of choosing the appropriate algorithm for each dataset. You'll apply unsupervised clustering algorithms over real-world datasets, to discover patterns and profiles, and explore the process to solve an unsupervised machine learning problem.
The focus of the book then shifts to supervised learning algorithms. You'll learn to implement different supervised algorithms and develop neural network structures using the scikit-learn package. You'll also learn how to perform coherent result analysis to improve the performance of the algorithm by tuning hyperparameters.
Ryan Marvin, Mark Ng’ang’a, Amos Omondi
ISBN 13: 9781789807325 Packt 324 Pages (October 2018)
Book Overview:
With an interesting mix of theory and practicals, explore Python and its features, and progress from beginner to being skilled in this popular scripting language
As you settle into the Python ecosystem, you'll learn about data structures and study ways to correctly store and represent information. By working through specific examples, you'll learn how Python implements object-oriented programming (OOP) concepts of abstraction, encapsulation of data, inheritance, and polymorphism. You'll be given an overview of how imports, modules, and packages work in Python, how you can handle errors to prevent apps from crashing, as well as file manipulation.
By the end of this book, you'll have built up an impressive portfolio of projects and armed yourself with the skills you need to tackle Python projects in the real world.
Python Data Science Essentials - Third Edition
Alberto Boschetti, Luca Massaron
ISBN 13: 9781789537864 Packt 472 pages(September 2018)
Book Overview:
Gain useful insights from your data using popular data science tools
Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries.
This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn. The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You’ll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost.
By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users.
Python Artificial Intelligence Projects for Beginners
Joshua Eckroth
ISBN 13: 9781789539462 Packt 162 Pages
Book Overview:
This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library.
By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress.
Samuel Bowne
ISBN 13: 9781789534443 Packt 100 Pages
Book Overview:
Learn to evaluate and compare data encryption methods and attack cryptographic systems
Cryptography is essential for protecting sensitive information, but it is often performed inadequately or incorrectly.
Hands-On Cryptography with Python starts by showing you how to encrypt and evaluate your data. The book will then walk you through various data encryption methods,such as obfuscation, hashing, and strong encryption, and will show how you can attack cryptographic systems. You will learn how to create hashes, crack them, and will understand why they are so different from each other. In the concluding chapters, you will use three NIST-recommended systems: the Advanced Encryption Standard (AES), the Secure Hash Algorithm (SHA), and the Rivest-Shamir-Adleman (RSA).
By the end of this book, you will be able to deal with common errors in encryption.
Hands-On Data Analysis with NumPy and Pandas
Curtis Miller
ISBN 13: 9781789530797 Packt 168 Pages (June 2018)
Book Overview:
Get to grips with the most popular Python packages that make Data Analysis possible
Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions.
You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation.
Deep Reinforcement Learning Hands-On
Maxim Lapan
ISBN 13: 9781788834247 Packt 546 Pages (June 2018)
Book Overview:
This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems.
Recent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google’s use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace.
Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on ‘grid world’ environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots.
Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy
ISBN 13: 9781786469786 Packt 320 Pages (April 2018)
Book Overview:
Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide.
Throughout the book, you’ll learn how to implement deep learning algorithms for machine learning systems and integrate them into your product offerings, including search, image recognition, and language processing. Additionally, you’ll learn how to analyze and improve the performance of deep learning models. This can be done by comparing algorithms against benchmarks, along with machine intelligence, to learn from the information and determine ideal behaviors within a specific context.
After finishing the book, you will be familiar with machine learning techniques, in particular the use of TensorFlow for deep learning, and will be ready to apply your knowledge to research or commercial projects.
Hands-On Transfer Learning with Python
Dipanjan Sarkar, Raghav Bali, Tamoghna Ghosh
ISBN 13: 9781788831307 Packt 438 Pages (August 2018)
Book Overview:
Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem
The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples.
The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with practical examples. In the concluding chapters, we will focus on a multitude of real-world case studies and problems associated with areas such as computer vision, audio analysis and natural language processing (NLP).
Mastering Python Design Patterns - Second Edition
Kamon Ayeva, Sakis Kasampalis
ISBN 13: 9781788837484 Packt 248 Pages (August 2018)
Book Overview:
Exploit various design patterns to master the art of solving problems using Python
This book takes you through a variety of design patterns and explains them with real-world examples. You will get to grips with low-level details and concepts that show you how to write Python code, without focusing on common solutions as enabled in Java and C++. You'll also fnd sections on corrections, best practices, system architecture, and its designing aspects. This book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems. You'll focus on most of the Gang of Four (GoF) design patterns, which are used to solve everyday problems, and take your skills to the next level with reactive and functional patterns that help you build resilient, scalable, and robust applications.
By the end of the book, you'll be able to effciently address commonly faced problems and develop applications, and also be comfortable working on scalable and maintainable projects of any size.
Tkinter GUI Application Development Blueprints, Second Edition
Bhaskar Chaudhary
ISBN 13: 9781788837460 Packt 422 Pages (March 2018)
Book Overview:
Geometry Management, Event Handling, and more
This book will help you master the art of GUI programming. It delivers the bigger picture of GUI programming by building real-world, productive, and fun applications such as a text editor, drum machine, game of chess, audio player, drawing application, piano tutor, chat application, screen saver, port scanner, and much more. In every project, you will build on the skills acquired in the previous project and gain more expertise. You will learn to write multithreaded programs, network programs, database-driven programs, asyncio based programming and more. You will also get to know the modern best practices involved in writing GUI apps.
With its rich source of sample code, you can build upon the knowledge gained with this book and use it in your own projects in the discipline of your choice.
Tkinter GUI Application Development Cookbook
Alejandro Rodas de Paz
ISBN 13: 9781788622301 Packt 242 Pages (March 2018)
Book Overview:
Discover solutions to all your Tkinter and Python GUI development problems
As one of the more versatile programming languages, Python is well-known for its batteries-included philosophy, which includes a rich set of modules in its standard library; Tkinter is the library included for building desktop applications. Due to this, Tkinter is a common choice for rapid GUI development, and more complex applications can benefit from the full capabilities of this library. This book covers all of your Tkinter and Python GUI development problems and solutions.
Tkinter GUI Application Development Cookbook starts with an overview of Tkinter classes and at the same time provides recipes for basic topics, such as layout patterns and event handling. Next, we cover how to develop common GUI patterns, such as entering and saving data, navigating through menus and dialogs, and performing long-running actions in the background.You can then make your apps leverage network resources effectively and perform graphical operations on a canvas and related tasks such as detecting collisions between items. Finally, this book covers using themed widgets, an extension of Tk widgets that have a more native look and feel. Finally, this book covers using the canvas and themed widgets.
Mike Driscoll
ISBN 13: 9781788399081 Packt 366 Pages (February 2018)
Book Overview:
Mike Driscoll takes you on a journey talking to a hall-of-fame list of truly remarkable Python experts. You'll be inspired every time by their passion for the Python language, as they share with you their experiences, contributions, and careers in Python.
Hear from these key Python thinkers about the current status of Python, and where it's heading in the future. Listen to their close thoughts on significant Python topics, such as Python's role in scientific computing, and machine learning. Understand the direction of Python, and what needs to change for Python 4
Each of these twenty Python Interviews can inspire and refresh your relationship with Python and the people who make Python what it is today. Let these interviews spark your own creativity, and discover how you also have the ability to make your mark on a thriving tech community. This book invites you to immerse in the Python landscape, and let these remarkable programmers show you how you too can connect and share with Python programmers around the world. Learn from their opinions, enjoy their stories, and use their tech tips.
OpenCV 3.x with Python By Example - Second Edition
Gabriel Garrido, Prateek Joshi
ISBN 13: 9781788396905 Packt 268 Pages (January 2018)
Book:
Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV.
We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples.
This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications.
scikit-learn Cookbook - Second Edition
Julian Avila, Trent Hauck
ISBN 13: 9781787286382 Packt 374 Pages (November 2017)
Book Overview:
Learn to use scikit-learn operations and functions for Machine Learning and deep learning applications.
This book includes walk throughs and solutions to the common as well as the not-so-common problems in machine learning, and how scikit-learn can be leveraged to perform various machine learning tasks effectively.
Theodore Petrou
ISBN 13: 9781784393878 Packt 538 Pages (October 2017)
Book Overview:
Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysis
This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way.
Indra den Bakker
ISBN 13: 9781787125193 Packt 330 Pages (October 2017)
Book Overview:
Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide
This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics.
The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras and CNTK is provided. The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios.
Python Digital Forensics Cookbook
Preston Miller, Chapin Bryce
ISBN 13: 9781783987467 Packt Publishing 412 Pages (September 2017)
Book Overview:
Over 60 recipes to help you learn digital forensics and leverage Python scripts to amplify your examinations.
By leveraging the Python recipes explored throughout this book, you make the complex simple, quickly extracting relevant information from large datasets. You will explore, develop, and deploy Python code and libraries to provide meaningful results that can be immediately applied to your investigations. Throughout the Python Digital Forensics Cookbook, recipes include topics such as working with forensic evidence containers, parsing mobile and desktop operating system artifacts, extracting embedded metadata from documents and executables, and identifying indicators of compromise. You will also learn to integrate scripts with Application Program Interfaces (APIs) such as VirusTotal and PassiveTotal, and tools such as Axiom, Cellebrite, and EnCase.
By the end of the book, you will have a sound understanding of Python and how you can use it to process artifacts in your investigations.
Practical Time Series Analysis
Dr. Avishek Pal, Dr. PKS Prakash
ISBN 13: 9781788290227 Packt Publishing 244 Pages (September 2017)
Book Overview:
Step by Step guide filled with real world practical examples.
The book starts with descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, you shift focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented, to develop accurate forecasting models for complex time series, and under the availability of little domain knowledge. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python.
The book concludes with the Appendix, with a brief discussion of programming and solving data science problems using Python.
Saurabh Kapur
ISBN 13: 9781788299763 Packt Publishing 206 Pages (August 2017)
Book Overview:
Unleash the power of computer vision with Python to carry out image processing and computer vision techniques
This book is a thorough guide for developers who want to get started with building computer vision applications using Python 3. The book is divided into five sections: The Fundamentals of Image Processing, Applied Computer Vision, Making Applications Smarter,Extending your Capabilities using OpenCV, and Getting Hands on. Throughout this book, three image processing libraries Pillow, Scikit-Image, and OpenCV will be used to implement different computer vision algorithms.
Learning Concurrency in Python
Elliot Forbes
ISBN 13: 9781787285378 Packt Publishing 313 Pages(August 2017)
Book Overview:
Practically and deeply understand concurrency in Python to write efficient programs
This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python.
The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems.
Learning pandas - Second Edition
Michael Heydt
ISBN 13: 9781787123137 Packt Publishing 446 pages (June 2017)
Book Overview:
With this book you will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance.
With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science.
What you will learn:
- Understand how data analysts and scientists think about of the processes of gathering and understanding data
- Learn how pandas can be used to support the end-to-end process of data analysis
Use pandas Series and DataFrame objects to represent single and multivariate data
- Slicing and dicing data with pandas, as well as combining, grouping, and aggregating data from multiple sources
- How to access data from external sources such as files, databases, and web services
- Represent and manipulate time-series data and the many of the intricacies involved with this type of data
- How to visualize statistical information
- How to use pandas to solve several common data representation and analysis problems within finance
Python GUI Programming Cookbook - Second Edition
Burkhard A. Meier
ISBN 13: 9781787129450 Packt Publishing 422 pages (May 2017)
Book Overview:
This book will guide you through the very basics of creating a fully functional GUI in Python with only a few lines of code. Each and every recipe adds more widgets to the GUIs we are creating. While the cookbook recipes all stand on their own, there is a common theme running through all of them.
What you will learn:
- Create the GUI Form and add widgets
- Arrange the widgets using layout managers
- Use object-oriented programming to create GUIs
- Create Matplotlib charts
- Use threads and talking to networks
- Talk to a MySQL database via the GUI
- Perform unit-testing and internationalizing the GUI
- Extend the GUI with third-party graphical libraries
- Get to know the best practices to create GUIs
Who this book is written for:
This book is for intermediate Python programmers who wish to enhance their Python skills by writing powerful GUIs in Python. As Python is such a great and easy to learn language, this book is also ideal for any developer with experience of other languages and enthusiasm to expand their horizon.
Python Data Structures and Algorithms
Benjamin Baka
ISBN 13: 9781786467355 Packt Publishing 310 pages (May 2017)
Book Overview:
In this book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data.
What you will learn:
- Gain a solid understanding of Python data structures.
- Build sophisticated data applications.
- Understand the common programming patterns and algorithms used in Python data science.
- Write efficient robust code.
Who this book is written for:
This book will appeal to all Python developers. A basic knowledge of Python is expected.
Python: End-to-end Data Analysis
Phuong Vothihong, Martin Czygan, Ivan Idris, Magnus Vilhelm Persson & Luiz Felipe Martins
ISBN 13: 9781788394697 Packt Publishing 931 pages (May 2017)
Book Overview:
This book will get you started with Python data analysis by introducing the basics of data analysis and supported Python libraries such as matplotlib, NumPy, and pandas. Create visualizations by choosing color maps, different shapes, sizes, and palettes then delve into statistical data analysis using distribution algorithms and correlations.
What you will learn:
- Understand the importance of data analysis and master its processing steps
Get comfortable using Python and its associated data analysis libraries such as Pandas, NumPy, and SciPy
- Clean and transform your data and apply advanced statistical analysis to create attractive visualizations
- Analyze images and time series data
- Mine text and analyze social networks
- Perform web scraping and work with different databases, Hadoop, and Spark
- Use statistical models to discover patterns in data
- Detect similarities and differences in data with clustering
- Work with Jupyter Notebook to produce publication-ready figures to be included in reports
Who this book is written for:
This course is for developers, analysts, and data scientists who want to learn data analysis from scratch. This course will provide you with a solid foundation from which to analyze data with varying complexity. A working knowledge of Python (and a strong interest in playing with your data) is recommended.
Python Machine Learning By Example
Yuxi (Hayden) Liu
ISBN 13: 9781783553112 Packt Publishing 254 pages (May 2017)
Book Overview:
This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation.
What you will learn:
- Exploit the power of Python to handle data extraction, manipulation, and exploration techniques
- Use Python to visualize data spread across multiple dimensions and extract useful features
- Dive deep into the world of analytics to predict situations correctly
- Implement machine learning classification and regression algorithms from scratch in Python
- Be amazed to see the algorithms in action
- Evaluate the performance of a machine learning model and optimize it
- Solve interesting real-world problems using machine learning and Python as the journey unfolds
Who this book is written for:
This book is for anyone interested in entering the data science stream with machine learning. Basic familiarity with Python is assumed.
Valentino Zocca, Gianmario Spacagna, Daniel Slater, Peter Roelants
ISBN 13: 9781786464453 Packt Publishing 406 pages (April 2017)
Book Overview:
The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.
What you will learn:
- Get a practical deep dive into deep learning algorithms
Explore deep learning further with Theano, Caffe, Keras, and TensorFlow
- Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines
- Dive into Deep Belief Nets and Deep Neural Networks
- Discover more deep learning algorithms with Dropout and Convolutional Neural Networks
- Get to know device strategies so you can use deep learning algorithms and libraries in the real world
Who this book is written for:
This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.
Software Architecture with Python
Anand Balachandran Pillai
ISBN 13: 9781786468529 Packt Publishing 556 pages (April 2017)
Book Overview:
This book starts off by explaining how Python fits into an application architecture. As you move along, you will understand the architecturally significant demands and how to determine them. Later, you’ll get a complete understanding of the different architectural quality requirements that help an architect to build a product that satisfies business needs, such as maintainability/reusability, testability, scalability, performance, usability, and security.
What you will learn:
- Build programs with the right architectural attributes
- Use Enterprise Architectural Patterns to solve scalable problems on the Web
- Understand design patterns from a Python perspective
- Optimize the performance testing tools in Python
- Deploy code in remote environments or on the Cloud using Python
- Secure architecture applications in Python
Who this book is written for:
This book is for experienced Python developers who are aspiring to become the architects of enterprise-grade applications or software architects who would like to leverage Python to create effective blueprints of applications.
Learning Data Mining with Python - Second Edition
Robert Layton
ISBN 13: 9781787126787 Packt Publishing 358 pages (April 2017)
Book Overview:
This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK.
What you will learn:
- Apply data mining concepts to real-world problems
- Predict the outcome of sports matches based on past results
- Determine the author of a document based on their writing style
- Use APIs to download datasets from social media and other online services
- Find and extract good features from difficult datasets
- Create models that solve real-world problems
- Design and develop data mining applications using a variety of datasets
- Perform object detection in images using Deep Neural Networks
- Find meaningful insights from your data through intuitive visualizations
- Compute on big data, including real-time data from the internet
Who this book is written for:
If you are a Python programmer who wants to get started with data mining, then this book is for you. If you are a data analyst who wants to leverage the power of Python to perform data mining efficiently, this book will also help you. No previous experience with data mining is expected.
Python Data Analysis - Second Edition
Armando Fandango
ISBN 13: 9781787127487 Packt Publishing 330 pages (March 2017)
Book Overview:
With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis.
What you will learn:
Install open source Python modules such NumPy, SciPy, Pandas, stasmodels, scikit-learn,theano, keras, and tensorflow on various platforms
- Prepare and clean your data, and use it for exploratory analysis
- Manipulate your data with Pandas
- Retrieve and store your data from RDBMS, NoSQL, and distributed filesystems such as HDFS and HDF5
- Visualize your data with open source libraries such as matplotlib, bokeh, and plotly
- Learn about various machine learning methods such as supervised, unsupervised, probabilistic, and Bayesian
- Understand signal processing and time series data analysis
- Get to grips with graph processing and social network analysis
Who this book is written for:
This book is for programmers, scientists, and engineers who have the knowledge of Python and know the basics of data science. It is for those who wish to learn different data analysis methods using Python 3.5 and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.
Python: Data Analytics and Visualization
Phuong Vo.T.H, Martin Czygan, Ashish Kumar, Kirthi Raman
ISBN 13: 9781788290098 Packt Publishing 866 pages (March 2017)
Book Overview:
Data analysis is the process of applying logical and analytical reasoning in order to study each data component. Python's powerful standard libraries or toolkits, such as Pylearn2 and Hebel, offer a fast, reliable, cross-platform environment for data analytics. This learning path will start with basic data analysis and you will then will gradually move on to increasingly complex problems; your journey will end with representing analyzed data in meaningful visualizations.
What you will learn:
Get acquainted with NumPy and use arrays and array-oriented computing in data analysis
- Process and analyze data using the time-series capabilities of Pandas
- Understand the statistical and mathematical concepts behind predictive analytics algorithms
- Data visualization with Matplotlib
Interactive plotting with NumPy, Scipy, and MKL functions
- Build financial models using Monte-Carlo simulations
- Create directed graphs and multi-graphs
- Advanced visualization with D3
Who this book is written for:
This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner.
Artificial Intelligence with Python
Prateek Joshi
ISBN 13: 9781786464392 Packt Publishing 446 pages (January 2017)
Book Overview:
Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that’s based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide!
What you will learn:
- Realize different classification and regression techniques
- Understand the concept of clustering and how to use it to automatically segment data
- See how to build an intelligent recommender system
- Understand logic programming and how to use it
- Build automatic speech recognition systems
- Understand the basics of heuristic search and genetic programming
- Develop games using Artificial Intelligence
- Learn how reinforcement learning works
- Discover how to build intelligent applications centered on images, text, and time series data
- See how to use deep learning algorithms and build applications based on it
Who this book is written for:
This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks.
Building Recommendation Engines
Suresh Kumar Gorakala
ISBN 13: 9781785884856 Packt Publishing 372 pages (December 2016)
Book Overview:
The book starts with an introduction to recommendation systems and its applications. You will then start building recommendation engines straight away from the very basics. As you move along, you will learn to build recommender systems with popular frameworks such as R, Python, Spark, Neo4j, and Hadoop. You will get an insight into the pros and cons of each recommendation engine and when to use which recommendation to ensure each pick is the one that suits you the best.
What you will learn:
- Build your first recommendation engine
- Discover the tools needed to build recommendation engines
- Dive into the various techniques of recommender systems such as collaborative, content-based, and cross-recommendations
- Create efficient decision-making systems that will ease your work
- Familiarize yourself with machine learning algorithms in different frameworks
- Master different versions of recommendation engines from practical code examples
- Explore various recommender systems and implement them in popular techniques with R,
Who this book is written for:
This book caters to beginners and experienced data scientists looking to understand and build complex predictive decision-making systems, recommendation engines using R, Python, Spark, Neo4j, and Hadoop.
Osvaldo Martin
ISBN 13: 9781785883804 Packt Publishing 284 pages (November 2016)
Book Overview:
The purpose of this book is to teach the main concepts of Bayesian data analysis. You will learn how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, to check models and validate them. This book begins presenting the key concepts of the Bayesian framework and the main advantages of this approach from a practical point of view. Moving on, you will explore the power and flexibility of generalized linear models and how to adapt them to a wide array of problems, including regression and classification. You will also look into mixture models and clustering data, and you will finish with advanced topics like non-parametrics models and Gaussian processes. With the help of Python and PyMC3 you will learn to implement, check and expand Bayesian models to solve data analysis problems.
- Understand the essentials Bayesian concepts from a practical point of view
- Learn how to build probabilistic models using the Python library PyMC3
- Acquire the skills to sanity-check your models and modify them if necessary
- Add structure to your models and get the advantages of hierarchical models
- Find out how different models can be used to answer different data analysis questions
- When in doubt, learn to choose between alternative models.
- Predict continuous target outcomes using regression analysis or assign classes using logistic and softmax regression.
- Learn how to think probabilistically and unleash the power and flexibility of the Bayesian framework
Who this book is written for:
Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement probabilistic models in their day to day projects. Programming experience with Python is essential. No previous statistical knowledge is assumed.
Python: Real World Machine Learning
By Prateek Joshi et al.
ISBN 13: 9781787123212 Packt Publishing 941 pages (November 2016)
Course Overview:
In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms.
The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you’ll acquire a broad set of powerful skills in the area of feature selection and feature engineering.
The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python.
This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice.
This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:
- Python Machine Learning Cookbook by Prateek Joshi
- Advanced Machine Learning with Python by John Hearty
- Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca Massaron
What you learn:
- Use predictive modeling and apply it to real-world problems
- Understand how to perform market segmentation using unsupervised learning
- Apply your new-found skills to solve real problems, through clearly-explained code for every technique and test
- Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms
- Increase predictive accuracy with deep learning and scalable data-handling techniques
- Work with modern state-of-the-art large-scale machine learning techniques
- Learn to use Python code to implement a range of machine learning algorithms and techniques
Who this course is for:
This Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected.
Coffee Break Python: 50 Workouts to Kickstart Your Rapid Code Understanding in Python
By Christian Mayer, September 2018, 191 pages ISBN-13: 978-1719846585
Coffee Break Python: 50 Workouts to Kickstart Your Rapid Code Understanding in Python
Little time to learn Python? This book shows you how to learn Python during your coffee break!
Coffee Break Python is a new step-by-step learning system where you repeatedly solve practical Python puzzles.
Educational research shows that practical low-stake puzzles and tests help you to learn faster, smarter, and better.
As you work through Coffee Break Python, your Python expertise will grow—one coffee at a time. The book is packed with 50 Python puzzles, 10 practical learning tips, 5 compressed cheat sheets, and 1 new way to measure your coding skills.
You will train wildly important Python topics such as
Arithmetic operations: integer & float division, and modular arithmetic;
- Language elements: branching, loops, keywords, and functions;
- Data structures: integer, float, string, list, set, dictionary, and graph;
- Sequence operators: indexing, concatenation, slicing, and built-in functions;
- Function *arguments: default *, arbitrary *, unpacking *, keyword *;
- Set operations: lambda, filter, map, and intersection functions; and
Algorithms: recursion, Fibonacci, matrix search, bubble sort, quick sort, lexicographical sort, guess & check, binary search, and graph traversal.
How good are your Python skills? As a bonus, you will track your individual Python coding skill level throughout the book.
This book is for you, if you are slightly beyond beginner-level in Python:
- Do you already have experience with another programming language—and now it’s time to tackle Python?
- Are you a professional engineer and want to brush up your Python skills?
- Are you a student and need to get better at Python for academic courses?
Introduction to Computer Science Using Python: A Computational Problem-Solving Focus
By Charles Dierbach, John Wiley & Sons, December 2012, 612 pages ISBN 13: 978-0-470-55515-6
Recommended by Guido van Rossum "This is not your average Python book ... The book is incredibly thorough: there are exercises throughout the text (not just at the end of each chapter), and it includes a plethora of examples, screenshots, tables, charts, diagrams, and photos ... I love the final chapter, which is an overview of the history of computing, starting with Charles Babbage and Ada Lovelace ... All in all, I think this book is a great text for anyone teaching CS1." Neopythonic
Recommended by Textbook Adopter Herbert Daly - University of Bedfordshire "As a University lecturer with considerable responsibility at level 1, I found this book to be an outstanding introduction to the world of computing and the Python language." Amazon Review
Features:
- Basics first approach
- Focus on computational problem solving, starting with Chapter 1
- Hands-on "Let's Try It" sections and self-test questions throughout the book
- Each chapter section contains a "Let's Apply It" example program
- Each chapter ends with the step-by-step development and demonstrated debugging techniques of a significant-size program
- Contains various end-of-chapter exercises and assignments, including simple programming exercises, assignments involving the modification of programs from within the chapter, and challenging program development problems
- Thirty-four page final chapter on the history of computing, starting with Charles Babbage, with over 65 historical images
- Python 3 Programmers' Reference at the end of the book for quick look-up of Python details
PROVIDED INSTRUCTOR MATERIALS:
- instructors' manual (with answers to chapter exercises and assignments)
- source code for all textbook examples
- solution code for program assignments
over 1,000 well-designed, PowerPoint slides, including every fundamental aspect of each chapter
- included test bank
Publisher's page (for instructors' request of an evaluation copy) cdierbach@towson.edu (for questions, and example textbook materials)
Building Skills in Object-Oriented Design
Steven F. Lott
How do you move from OO programming to OO design? Do a lot of design focused on building a sophisticated application program. This 269-page book has 43 chapters that will help you build OO design skills through the creation of a moderately complex family of application programs. This is a step-by-step guide to OO design and implementation using either the Java or Python programming languages.
http://homepage.mac.com/s_lott/books/oodesign.html
Problem Solving with Algorithms and Data Structures
- Brad Miller and David Ranum
1590280539, Franklin Beedle & Associates, December 2005
This is a textbook for a CS2 Data Structures Course.