Books

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

Data Jujitsu: The Art of Turning Data into Product
3.8 (193 Ratings)
Data Science in General

Data Jujitsu: The Art of Turning Data into Product

DJ Patil, 2012
DJ is the "Data Scientist in Residence" at Greylock Partners

Learn how to use a problem's "weight" against itself. Learn more about the problems before starting on the solutions—and use the findings to solve them, or determine whether the problems are worth solving at all.

python for everybody cover.jpg
Languages: Python
4.3 (312 Ratings)
Learning Languages

Python for Everybody

Dr. Charles R Severance, 2016

This book is designed to introduce students to programming and computational thinking through the lens of exploring data. You can think of Python as your tool to solve problems that are far beyond the capability of a spreadsheet.

Data Driven: Creating a Data Culture
3.8 (325 Ratings)
Forming Data Science Teams

Data Driven: Creating a Data Culture

DJ Patil,‎ Hilary Mason
Hilary Mason is the lead scientist at bit.ly, DJ is the "Data Scientist in Residence" at Greylock Partners

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.

An Introduction to Statistical Learning with Applications in R
4.6 (1553 Ratings)
Statistics

An Introduction to Statistical Learning with Applications in R

Gareth James, Daniela Witten, Trevor Hastie, & Robert Tibshirani, 2013

This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, and much more.

Building Data Science Teams
3.6 (303 Ratings)
Forming Data Science Teams

Building Data Science Teams

DJ Patil
DJ is the "Data Scientist in Residence" at Greylock Partners

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

Untitled-1.jpg
4.4 (7155 Ratings)

The Visual Display of Quantitative Information

Edward R. Tufte

Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction
4.4 (250 Ratings)
Statistics

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Trevor Hastie, Robert Tibshirani, & Jerome Friedman, 2008

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics.

Pattern Recognition and Machine Learning book cover
4.3 (1538 Ratings)

Pattern Recognition and Machine Learning

Christopher M. Bishop, 2006

This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible.

Python Cookbook
Languages: Python
4.2 (391 Ratings)
Learning Languages

Python Cookbook

David Beazley & Brian K. Jones, 2013

If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Packed with practical recipes written and tested with Python 3.3. For experienced Python developers.

Reinforcement Learning: An Introduction
4.5 (388 Ratings)
Data Mining and Machine Learning

Reinforcement Learning: An Introduction

Richard S. Sutton & Andrew G. Barto, 2012

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.

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