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 Milovanovi?, 2013
Python for Finance by Yuxing Yan, 2014
Python Text Processing with NLTK 2.0 Cookbook by Jacob Perkins, 2010