Books

These are some books written by members of the meetup.

Parallel R

Q. Ethan McCallum

Text Mining with R

Julia Silge & David Robinson

Learning R: A Step-by-Step Function Guide to Data Analysis

Richard Cotton

Feature Engineering and Selection: A Practical Approach for Predictive Models

Max Kuhn

Service-Oriented Design with Ruby and Rails

Paul Dix

Bandit Algorithms for Website Optimization

John Myles White

Machine Learning for Hackers

Drew Conway & John Myles White

Advanced R: Second Edition

Hadley Wickham

Testing R Code

Richard Cotton

Getting Started with D3

Mike Dewar

ggplot2: Elegant Graphics for Data Analysis (Use R!)

Hadley Wickham

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

Hadley Wickham

Deep Learning with R

JJ Allaire

Analyzing the Analyzers

Harlan Harris, Sean Patrick Murphy & Marck Vaisman

Python for Data Analysis

Wes McKinney

R for Everyone

Jared P. Lander

Applied Predictive Modeling

Max Kuhn & Kjell Johnson

A Computational Approach to Statistical Learning

Bryan Lewis and Michael Kane

Red State, Blue State, Rich State, Poor State

Andrew Gelman

Bad Data

Q. Ethan McCallum

Data Science at the Command Line

Jeroen Janssens

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman & Jennifer Hill

Machine Learning for Email

Drew Conway & John Myles White

Doing Data Science

Cathy O'Neil and Rachel Schutt

Learning R

Richard Cotton

R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics

JD Long

Data Analysis with R - Second Edition: A comprehensive guide to manipulating, analyzing, and visualizing data in R

Tony Fischetti

Teaching Statistics: A Bag of Tricks

Andrew Gelman & Deborah Nolan

A Computational Approach to Statistical Learning

Bryan Lewis and Michael Kane

A Quantitative Tour of the Social Sciences

Andrew Gelman & Jeronimo Cortina

Forecasting: principles and practice

Rob Hyndman

Bayesian Data Analysis

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

Pandas for Everyone: Python Data Analysis

Daniel Y. Chen

Testing R Code

Richard Cotton

Introduction to Empirical Bayes: Examples from Baseball Statistics

David Robinson

R Packages: Organize, Test, Document, and Share Your Code

Hadley Wichkam