Books

R for Everyone

Jared P. Lander

Applied Predictive Modeling

Max Kuhn & Kjell Johnson

Red State, Blue State, Rich State, Poor State

Andrew Gelman

A Quantitative Tour of the Social Sciences

Andrew Gelman & Jeronimo Cortina

Python for Data Analysis

Wes McKinney

Bayesian Data Analysis

Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari & Donald B. Rubin

Machine Learning for Hackers

Drew Conway & John Myles White

Doing Data Science

Cathy O'Neil and Rachel Schutt

Service-Oriented Design with Ruby and Rails

Paul Dix

Text Mining with R

Julia Silge & David Robinson

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman & Jennifer Hill

Analyzing the Analyzers

Harlan Harris, Sean Patrick Murphy & Marck Vaisman

Getting Started with D3

Mike Dewar

Parallel R

Q. Ethan McCallum

Data Science at the Command Line

Jeroen Janssens

Testing R Code

Richard Cotton

Teaching Statistics: A Bag of Tricks

Andrew Gelman & Deborah Nolan

Machine Learning for Email

Drew Conway & John Myles White

Pandas for Everyone: Python Data Analysis

Daniel Y. Chen

Bandit Algorithms for Website Optimization

John Myles White

Bad Data

Q. Ethan McCallum