60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more

By Brendan Martin, (LearnDataSci).

Pulled from the web, here is a great collection of eBooks. While every single book in this list is provided for free, if you find any particularly helpful consider purchasing the printed version. The authors spent a great deal of time putting these resources together and I’m sure they would all appreciate the support!

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Data Science in General

• An Introduction to Data Science
  Jeffrey Stanton, 2013
• School of Data Handbook
  School of Data, 2015
• Data Jujitsu: The Art of Turning Data into Product
  DJ Patil, 2012

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Interviews with Data Scientists

• The Data Science Handbook
  [Buy on Amazon]
  Carl Shan, Henry Wang, William Chen, & Max Song, 2015
• The Data Analytics Handbook
  Brian Liou, Tristan Tao, & Declan Shener, 2015

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Forming Data Science Teams

• Data Driven: Creating a Data Culture
  [Buy on Amazon]
  Hilary Mason & DJ Patil, 2015
• Building Data Science Teams
  [Buy on Amazon]
  DJ Patil, 2011
• Understanding the Chief Data Officer
  Julie Steele, 2015

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Data Analysis

• The Elements of Data Analytic Style
  [Buy on Amazon]
  Jeff Leek, 2015

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Distributed Computing Tools

• Hadoop: The Definitive Guide
  [Buy on Amazon]
  Tom White, 2011
• Data-Intensive Text Processing with MapReduce
  [Buy on Amazon]
  Jimmy Lin & Chris Dyer, 2010

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Learning Languages

Python

• Think Python: How to Think Like a Computer Scientist
  Allen Downey, 2012
• Python Programming
  Wikibooks, 2015
• Automate the Boring Stuff with Python: Practical Programming for Total Beginners
  [Buy on Amazon]
  Al Sweigart, 2015
• Learn Python the Hard Way
  [Buy on Amazon]
  Zed A. Shaw, 2013

R

• R Programming for Data Science 
  Roger D. Peng, 
• R Programming 
  Wikibooks, 2014
• Advanced R
  [Buy on Amazon]
  Hadley Wickham, 2014

SQL

• Learn SQL The Hard Way
  Zed. A. Shaw, 2010
• SQL Tutorial 
  Tutorials Point

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Data Mining and Machine Learning

• Introduction to Machine Learning 
  Amnon Shashua, 2008
• Machine Learning
  Abdelhamid Mellouk & Abdennacer Chebira, 450
• Machine Learning – The Complete Guide
  Wikipedia
• Social Media Mining An Introduction
  [Buy on Amazon]
  Reza Zafarani, Mohammad Ali Abbasi, & Huan Liu, 2014
• Data Mining: Practical Machine Learning Tools and Techniques
  [Buy on Amazon]
  Ian H. Witten & Eibe Frank, 2005
• Mining of Massive Datasets
  [Buy on Amazon]
  Jure Leskovec, Anand Rajaraman, & Jeff Ullman, 2014
• A Programmer’s Guide to Data Mining
  Ron Zacharski, 2015
• Data Mining with Rattle and R
  [Buy on Amazon]
  Graham Williams, 2011
• Data Mining and Analysis: Fundamental Concepts and Algorithms
  [Buy on Amazon]
  Mohammed J. Zaki & Wagner Meria Jr., 2014
• Probabilistic Programming & Bayesian Methods for Hackers
  [Buy on Amazon]
  Cam Davidson-Pilon, 2015
• Data Mining Techniques For Marketing, Sales, and Customer Relationship Management
  [Buy on Amazon]
  Michael J.A. Berry & Gordon S. Linoff, 2004
• Inductive Logic Programming: Techniques and Applications
  [Buy on Amazon]
  Nada Lavrac & Saso Dzeroski, 1994
• Pattern Recognition and Machine Learning
  [Buy on Amazon]
  Christopher M. Bishop, 2006
• Machine Learning, Neural and Statistical Classification
  [Buy on Amazon]
  D. Michie, D.J. Spiegelhalter, & C.C. Taylor, 1999
• Information Theory, Inference, and Learning Algorithms
  [Buy on Amazon]
  David J.C. MacKay, 2005
• Data Mining and Business Analytics with R
  [Buy on Amazon]
  Johannes Ledolter, 2013
• Bayesian Reasoning and Machine Learning
  [Buy on Amazon]
  David Barber, 2014
• Gaussian Processes for Machine Learning
  [Buy on Amazon]
  C. E. Rasmussen & C. K. I. Williams, 2006
• Reinforcement Learning: An Introduction
  [Buy on Amazon]
  Richard S. Sutton & Andrew G. Barto, 2012
• Algorithms for Reinforcement Learning
  [Buy on Amazon]
  Csaba Szepesvari , 2009
• Big Data, Data Mining, and Machine Learning
  [Buy on Amazon]
  Jared Dean, 2014
• Modeling With Data
  [Buy on Amazon]
  Ben Klemens, 2008
• KB – Neural Data Mining with Python Sources
  [Buy on Amazon]
  Roberto Bello, 2013
• Deep Learning
  Yoshua Bengio, Ian J. Goodfellow, & Aaron Courville, 2015
• Neural Networks and Deep Learning
  Michael Nielsen, 2015
• Data Mining Algorithms In R
  Wikibooks, 2014
• Data Mining and Analysis: Fundamental Concepts and Algorithms
  [Buy on Amazon]
  Mohammed J. Zaki & Wagner Meira Jr., 2014
• Theory and Applications for Advanced Text Mining
  Shigeaki Sakurai, 2012

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Statistics and Statistical Learning

• Think Stats: Exploratory Data Analysis in Python
  [Buy on Amazon]
  Allen B. Downey, 2014
• Think Bayes: Bayesian Statistics Made Simple
  [Buy on Amazon]
  Allen B. Downey, 2012
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction
  [Buy on Amazon]
  Trevor Hastie, Robert Tibshirani, & Jerome Friedman, 2008
• An Introduction to Statistical Learning with Applications in R
  [Buy on Amazon]
  Gareth James, Daniela Witten, Trevor Hastie, & Robert Tibshirani, 2013
• A First Course in Design and Analysis of Experiments
  [Buy on Amazon]
  Gary W. Oehlert, 2010

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Data Visualization

• D3 Tips and Tricks
  [Buy on Amazon]
  Malcolm Maclean, 2015
• Interactive Data Visualization for the Web
  [Buy on Amazon]
  Scott Murray, 2013

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Big Data

• Disruptive Possibilities: How Big Data Changes Everything [Buy on Amazon]
  Jeffrey Needham, 2013
• Real-Time Big Data Analytics: Emerging Architecture
  [Buy on Amazon]
  Mike Barlow, 2013
• Big Data Now: 2012 Edition
  [Buy on Amazon]
  O’Reilly Media, Inc., 2012

Computer Science Topics

• Natural Language Processing with Python [Buy on Amazon]
  Steven Bird, 2009
• Computer Vision [Buy on Amazon]
  Richard Szeliski, 2010
• Concise Computer Vision [Buy on Amazon]
  Reinhard Klette, 2010
• Artificial Intelligence A Modern Approach, 1st Edition
  [Buy on Amazon (3rd Edition)]
  Stuart Russell, 1995

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Well, there you have it. Thousands of e-pages to read through. We hope there’s something there for everyone, no matter what level you’re starting at. If you have any suggestions of free books to include or want to review a book mentioned, please comment below and let us know!

Original.

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