All | (Big) Data Analytics | Algorithms | Artificial Intelligence | Bayesian Networks | Business & Strategy | Computer Vision | Data Journalism | Data Mining | Data Scientists | Data Structures | Data Visualization | General Data Science | Hadoop, MapReduce | Information Retrieval | Linear Regression | Linguistic | Machine Learning, Predictive Analytics | Math | Metadata | Natural Language Processing | Network Science | Other Sites with Free Data Science Resources | Probability | Python | R | Singularity/Transhumanism | Statistics | Text Mining

Streaming Systems: The what, where, when, and how of large-scale data processing.The Little MongoDB Book.

Foundations of Data Science.

Dive into Python 3.

Artificial Intelligence: A Modern Approach.

An Introduction to Statistical Learning with Applications in R.

Hadoop Explained: An introduction to the most popular big data platform in the world.

A Byte of Python.

Time Series Analysis and Its Applications with R Examples.

The R Inferno.

NoSQL Databases.

Linear Algebra.

Probability and Statistics Cookbook.

Mastering Apache Spark.

A First Course in Linear Algebra.

The Definitive Guide to Graph Databases for the RDBMS Developer.

A Little Book of R For Time Series.

Hadoop Big Data Analysis Framework.

Extracting Data from NoSQL Databases: A step towards interactive visual analysis of NoSQL data.

Spatial Epidemiology Notes: Applications and Vignettes in R.

Ecological Models and Data in R.

Programming Computer Vision with Python.

Think Python: How to think like a computer scientist.

MongoDB Succinctly.

A Little Book of R For Multivariate Analysis.

Deep Learning Architectures for AI.

Introductory Statistics with Randomization and Simulation.

Practical Regression and Anova using R.

Cassandra Query Language.

A Little Book of R For Biomedical Statistics.

Elementary Differential Equations.

Real-World Active Learning: Application and strategies for human-in-the-loop machine learning.

Python for Informatics: Exploring Information.

Graph Databases: New opportunities for connected data.

The LION Way: Machine learning plus intelligent optimization.

How to Think Like a Computer Scientist: Learning with Python 3 documentation.

Programming Pig. Covers almost every feature of Pig: different modes it can be run in, complete coverage of the Pig Latin language, and how to extend Pig with your own User Defined Functions (UDFs)

Test-Driven Development with Python. A complete best-practices crash course, from start to finish, into modern web application development with Python

Making Games with Python & Pygame. Covers the Pygame library with the source code for 11 games such as Nibbles, Tetris, Simon, Bejeweled, Othello, Connect Four, Flood It, and others

Invent Your Own Computer Games with Python, 4th Edition. Great introduction to Python and a great introduction to building fairly simple but interesting games

Cracking Codes with Python. Teaches complete beginners how to program in the Python programming language and features the source code to several ciphers and hacking programs for these ciphers

Python Practice Book.

Learn Python, Break Python. A hands-on introduction to the Python programming language, written for people who have no experience with programming whatsoever

Python Cookbook. This book is aimed at more experienced Python programmers who are looking to deepen their understanding of the language and modern programming idioms

Welcome to Python for you and me. A simple book to learn Python programming language, it is for the programmers who are new to Python.

The R Manuals.

R by Example.

SQL for Web Nerds.

CouchDB: The definitive guide. Shows you how to use this document-oriented database as a standalone application framework or with high-volume, distributed applications

Linear Algebra. This book attempts to build students up to the point where they have a grasp of the clear and precise nature of mathematics