Books

These are some books written by members of the meetup.

Machine Learning for Email

Drew Conway & John Myles White

Forecasting: principles and practice

Rob Hyndman

Service-Oriented Design with Ruby and Rails

Paul Dix

A Quantitative Tour of the Social Sciences

Andrew Gelman & Jeronimo Cortina

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

JD Long

Bandit Algorithms for Website Optimization

John Myles White

Bad Data

Q. Ethan McCallum

Data Science at the Command Line

Jeroen Janssens

Parallel R

Q. Ethan McCallum

Advanced R: Second Edition

Hadley Wickham

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

Richard Cotton

Bayesian Data Analysis

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

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

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

Hadley Wickham

R for Everyone

Jared P. Lander

Learning R

Richard Cotton

Testing R Code

Richard Cotton

Text Mining with R

Julia Silge & David Robinson

Analyzing the Analyzers

Harlan Harris, Sean Patrick Murphy & Marck Vaisman

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman & Jennifer Hill

Applied Predictive Modeling

Max Kuhn & Kjell Johnson

Teaching Statistics: A Bag of Tricks

Andrew Gelman & Deborah Nolan

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

Hadley Wichkam

Red State, Blue State, Rich State, Poor State

Andrew Gelman

Getting Started with D3

Mike Dewar

Python for Data Analysis

Wes McKinney

Deep Learning with R

JJ Allaire

Data Science on AWS

Chris Fregly & Antje Barth

Machine Learning for Hackers

Drew Conway & John Myles White

Doing Data Science

Cathy O'Neil & Rachel Schutt

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

Hadley Wickham

Feature Engineering and Selection: A Practical Approach for Predictive Models

Max Kuhn

Pandas for Everyone: Python Data Analysis

Daniel Y. Chen

A Computational Approach to Statistical Learning

Bryan Lewis and Michael Kane