Drew Conway

Drew Conway

Hopeful academic, data nerd, average hacker, student of conflict.

New York, New York

Areas of Expertise:

  • R
  • Python
  • Machine Learning
  • Visualization
  • consulting
  • speaking
  • training
Drew Conway is a PhD candidate in Politics at NYU. He studies international relations, conflict, and terrorism using the tools of mathematics, statistics, and computer science in an attempt to gain a deeper understanding of these phenomena. His academic curiosity is informed by his years as an analyst in the U.S. intelligence and defense communities.

Machine Learning for Hackers Machine Learning for Hackers
by Drew Conway , John Myles White
February 2012
Print: $39.99
Ebook: $31.99

Machine Learning for Email Machine Learning for Email
by Drew Conway , John Myles White
October 2011
Print: $24.99
Ebook: $14.99

Predicting the Future Predicting the Future
by Drew Conway , Christopher Ahlberg , Robert McGrew , Rion Snow
February 2011
OUT OF PRINT

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 you’re 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 you’re 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 you’re looking for a hands-on introduction to machine learning, maybe as a prelude to or complement to a more theoretical text, you’ll 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