Books

These are some books written by members of the meetup.

Red State, Blue State, Rich State, Poor State

Andrew Gelman

Bayesian Data Analysis

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

Learning R

Richard Cotton

Machine Learning for Email

Drew Conway & John Myles White

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

Hadley Wichkam

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

Richard Cotton

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

Tony Fischetti

R for Everyone

Jared P. Lander

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman & Jennifer Hill

A Quantitative Tour of the Social Sciences

Andrew Gelman & Jeronimo Cortina

Forecasting: principles and practice

Rob Hyndman

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

JD Long

Bandit Algorithms for Website Optimization

John Myles White

Data Science at the Command Line

Jeroen Janssens

Analyzing the Analyzers

Harlan Harris, Sean Patrick Murphy & Marck Vaisman

Testing R Code

Richard Cotton

A Computational Approach to Statistical Learning

Bryan Lewis and Michael Kane

Getting Started with D3

Mike Dewar

Data Science on AWS

Chris Fregly & Antje Barth

Service-Oriented Design with Ruby and Rails

Paul Dix

Deep Learning with R

JJ Allaire

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

Hadley Wickham

Bad Data

Q. Ethan McCallum

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

Hadley Wickham

Doing Data Science

Cathy O'Neil & Rachel Schutt

Text Mining with R

Julia Silge & David Robinson

Feature Engineering and Selection: A Practical Approach for Predictive Models

Max Kuhn

Python for Data Analysis

Wes McKinney

Teaching Statistics: A Bag of Tricks

Andrew Gelman & Deborah Nolan

Advanced R: Second Edition

Hadley Wickham

Parallel R

Q. Ethan McCallum

Machine Learning for Hackers

Drew Conway & John Myles White

Introduction to Empirical Bayes: Examples from Baseball Statistics

David Robinson

Applied Predictive Modeling

Max Kuhn & Kjell Johnson

Pandas for Everyone: Python Data Analysis

Daniel Y. Chen