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