John Myles White is a Ph.D. student in the Princeton Psychology Department, where he studies how humans make decisions both theoretically and experimentally.
Outside of academia, John has been heavily involved in the data science movement, which has pushed for an open source software approach to data analysis. He is also the lead maintainer for several popular R packages, including ProjectTemplate and log4r.
Webcast: An Introduction to Machine Learning for Hackers September 18, 2012
We'll introduce programmers to two of the most common tools in the machine learning toolkit: linear regression and logistic regression. We'll show how these two tools let you make a first pass at solving almost any machine learning problem you might...
"If youre looking for a very solid, well written, overview of machine learning in R, Machine Learning for Hackers is a great starting point, as long as youre willing to read around the subject (the recommended texts and books cited list works well)."
--Jonathan Hammler, Compsoc -- Durham University Computing Society
"I recommend this book to anyone with interest in machine learning with a statistics background."
--Nilesh Thatte, BCS
"If youre looking for a hands-on introduction to machine learning, maybe as a prelude to or complement to a more theoretical text, youll enjoy this book."
--John D. Cook, The Endeavour
"I recommend it to any programmer who needs to generate predictions or classifications from data -- using R and learning more about the statistical techniques behind the methods will help you to create better data hacking applications in the long run."
--David Smith, Revolution Analytics