Who this book is for

This book is hands-on and low on theory. You should have better than beginner Python knowledge and have some knowledge of linear algebra, calculus, machine learning and statistics. Ideally, you would have read Python Data Analysis, but this is not a requirement. I also recommend the following books:

• Building Machine Learning Systems with Python by Willi Richert and Luis Pedro Coelho, 2013
• Learning NumPy Array by Ivan Idris, 2014
• Learning scikit-learn: Machine Learning in Python by Guillermo Moncecchi, 2013
• Learning SciPy for Numerical and Scientific Computing by Francisco J. Blanco-Silva, 2013
• Matplotlib for Python Developers by Sandro Tosi, 2009
• NumPy Beginner's Guide - Third Edition by Ivan Idris, 2015
• NumPy Cookbook – Second Edition by Ivan Idris, 2015
• Parallel Programming with Python by Jan Palach, 2014
• Python Data Visualization Cookbook by Igor Milovanović, 2013
• Python for Finance by Yuxing Yan, 2014
• Python Text Processing with NLTK 2.0 Cookbook by Jacob Perkins, 2010