The best books on Data Science, Big Data, Data Mining, Machine Learning, Python, R, SQL, NoSQL and more.

Data Mining and Machine Learning

A clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.

Forming Data Science Teams

In this in-depth report, data scientist DJ Patil explains the skills,perspectives, tools and processes that position data science teams for success.

Statistics

This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.

Forming Data Science Teams

In this O’Reilly report, DJ Patil and Hilary Mason outline the steps you need to take if your company is to be truly data-driven—including the questions you should ask and the methods you should adopt.

Learning Languages

This is a hands-on guide to Python 3 and its differences from Python 2. Each chapter starts with a real, complete code sample, picks it apart and explains the pieces, and then puts it all back together in a summary at the end.

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models.

Learning Languages

This is a free sample of Learn Python 2 The Hard Way with 8 exercises and Appendix A available for you to review.

Learning Languages

"Invent Your Own Computer Games with Python" teaches you computer programming in the Python programming language. Each chapter gives you the complete source code for a new game and teaches the programming concepts from these examples.

Learning Languages

By taking you through the development of a real web application from beginning to end, this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python.

Data Mining and Machine Learning

Offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations.