Books

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

The Data Science Handbook
4.1 (25 Ratings)
Interviews with Data Scientists

The Data Science Handbook

by Carl Shan (Author),‎ William Chen (Author),‎ Henry Wang (Author),‎ Max Song (Author)
25 Data Scientists contributed

The Data Science Handbook is a compilation of in-depth interviews with 25 remarkable data scientists, where they share their insights, stories, and advice.

Python Cookbook
Languages: Python
4.2 (377 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.

Learn Python the Hard Way
Languages: Python
3.9 (132 Ratings)
Learning Languages

Learn Python the Hard Way

Zed A. Shaw, 2013

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

Automate the Boring Stuff with Python: Practical Programming for Total Beginners
Languages: Python
4.3 (1444 Ratings)
Learning Languages

Automate the Boring Stuff with Python: Practical Programming for Total Beginners

Al Sweigart, 2015

Practical programming for total beginners. In Automate the Boring Stuff with Python, you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand-no prior programming experience required.

Computer Age Statistical Inference Book Cover
4.4 (68 Ratings)

Computer Age Statistical Inference: Algorithms, Evidence and Data Science

Bradley Efron, Trevor Hastie

The book integrates methodology and algorithms with statistical inference, and ends with speculation on the future direction of statistics and data science.

Artificial Intelligence A Modern Approach, 1st Edition
4.2 (331 Ratings)
Artificial Intelligence

Artificial Intelligence A Modern Approach, 1st Edition

Stuart Russell, 1995

Comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.

Information Theory, Inference, and Learning Algorithms
4.5 (380 Ratings)
Data Mining and Machine Learning

Information Theory, Inference, and Learning Algorithms

David J.C. MacKay, 2005

"Essential reading for students of electrical engineering and computer science; also a great heads-up for mathematics students concerning the subtlety of many commonsense questions." Choice

Bayesian Methods for Hackers
Languages: Python
4.1 (119 Ratings)
Data Mining and Machine Learning

Probabilistic Programming & Bayesian Methods for Hackers

Cam Davidson-Pilon, 2015

illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments.

data-analysis-using-regression.jpg
4.3 (244 Ratings)

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman, Jennifer Hill

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.

Computer Vision
4.2 (98 Ratings)
Computer Science Topics

Computer Vision

Richard Szeliski, 2010

Challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which you can use on you own personal media

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