Books

These are some books written by members of the meetup.

A Quantitative Tour of the Social Sciences

Andrew Gelman & Jeronimo Cortina

R for Everyone

Jared P. Lander

Learning R

Richard Cotton

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

Hadley Wickham

Teaching Statistics: A Bag of Tricks

Andrew Gelman & Deborah Nolan

Doing Data Science

Cathy O'Neil and Rachel Schutt

Testing R Code

Richard Cotton

Testing R Code

Richard Cotton

Getting Started with D3

Mike Dewar

Feature Engineering and Selection: A Practical Approach for Predictive Models

Max Kuhn

Advanced R: Second Edition

Hadley Wickham

Machine Learning for Hackers

Drew Conway & John Myles White

Service-Oriented Design with Ruby and Rails

Paul Dix

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

Tony Fischetti

Introduction to Empirical Bayes: Examples from Baseball Statistics

David Robinson

Text Mining with R

Julia Silge & David Robinson

Deep Learning with R

JJ Allaire

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

Hadley Wickham

Bandit Algorithms for Website Optimization

John Myles White

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

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

Hadley Wichkam

Machine Learning for Email

Drew Conway & John Myles White

Parallel R

Q. Ethan McCallum

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman & Jennifer Hill

Forecasting: principles and practice

Rob Hyndman

A Computational Approach to Statistical Learning

Bryan Lewis and Michael Kane

Data Science at the Command Line

Jeroen Janssens

Analyzing the Analyzers

Harlan Harris, Sean Patrick Murphy & Marck Vaisman

A Computational Approach to Statistical Learning

Bryan Lewis and Michael Kane

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

JD Long

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

Richard Cotton

Bad Data

Q. Ethan McCallum

Red State, Blue State, Rich State, Poor State

Andrew Gelman

Python for Data Analysis

Wes McKinney

Applied Predictive Modeling

Max Kuhn & Kjell Johnson