Books

These are some books written by members of the meetup.

Bad Data

Q. Ethan McCallum

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman & Jennifer Hill

Machine Learning for Email

Drew Conway & John Myles White

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

Hadley Wickham

Pandas for Everyone: Python Data Analysis

Daniel Y. Chen

Getting Started with D3

Mike Dewar

Bandit Algorithms for Website Optimization

John Myles White

Red State, Blue State, Rich State, Poor State

Andrew Gelman

Parallel R

Q. Ethan McCallum

Teaching Statistics: A Bag of Tricks

Andrew Gelman & Deborah Nolan

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

Richard Cotton

Advanced R: Second Edition

Hadley Wickham

Deep Learning with R

JJ Allaire

Data Science at the Command Line

Jeroen Janssens

Analyzing the Analyzers

Harlan Harris, Sean Patrick Murphy & Marck Vaisman

Forecasting: principles and practice

Rob Hyndman

R for Everyone

Jared P. Lander

Bayesian Data Analysis

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

Introduction to Empirical Bayes: Examples from Baseball Statistics

David Robinson

Learning R

Richard Cotton

A Quantitative Tour of the Social Sciences

Andrew Gelman & Jeronimo Cortina

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

Tony Fischetti

Python for Data Analysis

Wes McKinney

Doing Data Science

Cathy O'Neil & Rachel Schutt

Applied Predictive Modeling

Max Kuhn & Kjell Johnson

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

JD Long

Feature Engineering and Selection: A Practical Approach for Predictive Models

Max Kuhn

A Computational Approach to Statistical Learning

Bryan Lewis and Michael Kane

Machine Learning for Hackers

Drew Conway & John Myles White

Service-Oriented Design with Ruby and Rails

Paul Dix

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

Hadley Wichkam

Data Science on AWS

Chris Fregly & Antje Barth

Testing R Code

Richard Cotton

Text Mining with R

Julia Silge & David Robinson

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

Hadley Wickham