|
Size: 191
Comment: Create page
|
Size: 2374
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 1: | Line 1: |
| '''Python Scripting for Computational Science''' Hans Petter Langtangen |
'''A Primer on Scientific Programming with Python''' |
| Line 4: | Line 3: |
| ISBN:3540435085 Springer-Verlag, 726 pages (2004) |
. Hans Petter Langtangen |
| Line 8: | Line 5: |
| [http://www.springeronline.com/3-540-43508-5 Home Page] | ISBN: ISBN:3642024742, Springer, 693 pages (July 2009) |
| Line 10: | Line 7: |
| An example- and problem-oriented introduction to computer programming of scientific applications. ---- '''NumPy 1.5 Beginner's Guide''' . Ivan Idris ISBN: ISBN:1849515301, Packt Publishing, 234 pages (November 2011) An action-packed guide for the easy-to-use, high performance, Python based free open source NumPy mathematical library using real-world examples. ---- '''Participatory Geospatial Development Using Python''' . Ravish Bapna ISBN: ISBN:1479316474, CreateSpace, 146 pages (September 2012) The book contains discussion on raster and vector data processing using Python binding of GDAL/OGR library. Also, different approaches of representing spatial reference system are enumerated. There is a discussion on LIDAR data processing using Python binding of libLAS library. Apart from processing geospatial data, the book also covers plotting of geospatial data. The last chapter deals with freely available geospatial data, such as ASTER GDEM, SRTM data etc. ---- '''[[http://www.packtpub.com/building-machine-learning-systems-with-python/book|Building Machine Learning Systems with Python]]''' . Willi Richert and Luis Pedro Coelho ISBN: [[http://www.packtpub.com/building-machine-learning-systems-with-python/book|1782161406]], PACKT Publishing, 350 pages (September 2013) * A practical, scenario-based tutorial to get into the right mind set of a machine learner (data exploration) * Master the diverse ML Python libraries and start building your Python-based ML systems * Wide and practical coverage of ML areas to immediately implement in your projects - Classification, Regression, Recommender Systems, Computer Vision, and much more ---- '''[[http://www.packtpub.com/python-for-finance/book|Python for Finance]]''' . Yuxing Yan ISBN: [[http://www.packtpub.com/python-for-finance/book|1783284374]], PACKT Publishing, 408 pages (April 2014) * Estimate market risk, form various portfolios, and estimate their variance-covariance matrixes using real-world data * Explains many financial concepts and trading strategies with the help of graphs * A step-by-step tutorial with many Python programs that will help you learn how to apply Python to finance |
A Primer on Scientific Programming with Python
- Hans Petter Langtangen
ISBN: 3642024742, Springer, 693 pages (July 2009)
An example- and problem-oriented introduction to computer programming of scientific applications.
NumPy 1.5 Beginner's Guide
- Ivan Idris
ISBN: 1849515301, Packt Publishing, 234 pages (November 2011)
An action-packed guide for the easy-to-use, high performance, Python based free open source NumPy mathematical library using real-world examples.
Participatory Geospatial Development Using Python
- Ravish Bapna
ISBN: 1479316474, CreateSpace, 146 pages (September 2012)
The book contains discussion on raster and vector data processing using Python binding of GDAL/OGR library. Also, different approaches of representing spatial reference system are enumerated. There is a discussion on LIDAR data processing using Python binding of libLAS library. Apart from processing geospatial data, the book also covers plotting of geospatial data. The last chapter deals with freely available geospatial data, such as ASTER GDEM, SRTM data etc.
Building Machine Learning Systems with Python
- Willi Richert and Luis Pedro Coelho
ISBN: 1782161406, PACKT Publishing, 350 pages (September 2013)
- A practical, scenario-based tutorial to get into the right mind set of a machine learner (data exploration)
- Master the diverse ML Python libraries and start building your Python-based ML systems
- Wide and practical coverage of ML areas to immediately implement in your projects - Classification, Regression, Recommender Systems, Computer Vision, and much more
- Yuxing Yan
ISBN: 1783284374, PACKT Publishing, 408 pages (April 2014)
- Estimate market risk, form various portfolios, and estimate their variance-covariance matrixes using real-world data
- Explains many financial concepts and trading strategies with the help of graphs
- A step-by-step tutorial with many Python programs that will help you learn how to apply Python to finance