List of Free Learning Resources for Data Science, Machine Learning & Big Data: According to Github

This list contains free learning resources for data science, machine learning and big data related concepts, techniques, and applications. Inspired by Free Programming Books.

Each entry provides the expected audience for the certain book (beginner, intermediate, or veteran). It may be subjective, but it provides some clue of how difficult the book is.

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Index

Data Science Application

Data Visualization

Data Science Introduction

Data Science: An Introduction - Wikibook - Beginner
Disruptive Possibilities: How Big Data Changes Everything - Jeffrey Needham - Beginner
Introduction to Data Science - Jeffery Stanton - Beginner
Real-Time Big Data Analytics: Emerging Architecture - Mike Barlow - Beginner
The Evolution of Data Products - Mike Loukides - Beginner
The Promise and Peril of Big Data - David Bollier - Beginner

Data Processing

Data-Intensive Text Processing with MapReduce - Jimmy Lin and Chris Dyer - Intermediate

Data Analysis

Fundamentals

Fundamental Numerical Methods and Data Analysis - George W. Collins - Beginner
Introduction to Metadata - Murtha Baca - Beginner
Introduction to R - Notes on R: A Programming Environment for Data Analysis and Graphics - W. N. Venables, D. M. Smith, and the R Core Team - Beginner
Modeling with Data: Tools and Techniques for Scientific Computing - Ben Klemens - Beginner

Network Analysis

Introduction to Social Network Methods - Robert A. Hanneman and Mark Riddle - Intermediate
Networks, Crowds, and Markets: Reasoning About a Highly Connected World - David Easley and Jon Kleinberg - Intermediate
Network Science - Sarah Morrison - Beginner
The Wealth of Networks - Yochai Benkler - Beginner

Statistics

Advanced Data Analysis from an Elementary Point of View - Cosma Rohilla Shalizi - Veteran
An Introduction to R - W. N. Venables, D. M. Smith, and the R Core Team - Beginner
Analyzing Linguistic Data: a practical introduction to statistics - R. H. Baayan - Beginner
Applied Data Science - Ian Langmore and Daniel Krasner - Intermediate
Concepts and Applications of Inferential Statistics - Richard Lowry - Beginner
Forecasting: Principles and Practice - Rob J. Hyndman and George Athanasopoulos - Intermediate
Introduction to Probability - Charles M. Grinstead and J. Laurie Snell - Beginner
Introduction to Statistical Thought - Michael Lavine - Beginner
OpenIntro Statistics - Second Edition - David M. Diez, Christopher D. Barr, and Mine Cetinkaya-Rundel - Beginner
simpleR - Using R for Introductory Statistics - John Verzani - Beginner
Statistics - Beginner
Think Stats: Probability and Statistics for Programmers v2.0 - Allen B. Downey - Beginner
Computer Age Statistical Inference: Algorithms, Evidence and Data Science - Bradley Efron and Trevor Hastie - Intermediate

Data Mining

Data Mining and Analysis: Fundamental Concepts and Algorithms - Mohammed J. Zaki and Wagner Meira Jr. - Intermediate
Data Mining and Knowledge Discovery in Real Life Applications - Julio Ponce and Adem Karahoca - Beginner
Data Mining for Social Network Data - Springer - Veteran
Mining of Massive Datasets - Anand Rajaraman, Jure Leskovec, and Jeffrey D. Ullman - Intermediate
Knowledge-Oriented Applications in Data Mining - Kimito Funatsu - Intermediate
New Fundamental Technologies in Data Mining - Kimito Funatsu - Intermediate
R and Data Mining: Examples and Case Studies - Yanchang Zhao - Beginner
The Elements of Statistical Learning - Trevor Hastie, Robert Tibshirani, and Jerome Friedman - Intermediate
Theory and Applications for Advanced Text Mining - Shigeaki Sakurai - Intermediate

Machine Learning

A Course in Machine Learning - Hal Daume - Beginner
The First Encounter with Machine Learning - Max Welling - Beginner
Bayesian Reasoning and Machine Learning - David Barber - Veteran
Gaussian Processes for Machine Learning - Carl Edward Rasmussen and Christopher K. I. Williams - Veteran
Introduction to Machine Learning - Alex Smola and S.V.N. Vishwanathan - Intermediate
Probabilistic Programming & Bayesian Methods for Hackers - Cam Davidson-Pilon (main author) - Intermediate
The LION Way: Machine Learning plus Intelligent Optimization - Robert Battiti and Mauro Brunato - Intermediate
Thinking Bayes - Allen B. Downey - Beginner
Sklearn Basics - Beginner
Deep Learning - Ian Goodfellow, Yoshua Bengio and Aaron Courville - Intermediate

Data Science Application

Information Retrieval

Introduction to Information Retrieval - Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schutze - Intermediate

Data Visualization

Interactive Data Visualization for the Web - Scott Murray - Beginner
Plotting and Visualization in Python - Beginner

Uncategorized

Data Journalism Handbook - Jonathan Gray, Liliana Bounegru, and Lucy Chambers - Beginner
Building Data Science Teams - DJ Patil - Beginner
Information Theory, Inference, and Learning Algorithms - David MacKay - Intermediate
Mathematics for Computer Science - Eric Lehman, Thomas Leighton, and Albert R. Meyer - Beginner
The Field Guide to Data Science - Beginner

MOOCs about Data Science

Data Mining with Weka - Ian H. Witten - Intermediate
Mining Massive Datasets - Jeff Ullman, Jure Leskovec, Anand Rajaraman (Coursera) - Beginner
Introduction to Data Science - Bill Howe (Coursera) - Beginner
Introduction to Hadoop and MapReduce - Udacity - Beginner
Machine Learning - Andrew Ng (Coursera) - Beginner
Machine Learning Video Library - Yaser Abu-Mostafa - Intermediate
Natural Language Processing - Dan Jurafsky and Christopher Manning (Coursera) - Intermediate
Social and Economic Networks: Models and Analysis - Matthew O. Jackson (Coursera) - Intermediate
Social Network Analysis - Lada Adamic (Coursera) - Intermediate

Source: HOB

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