If you're an experienced programmer willing to crunch data, this concise guide will show you how to use machine learning to work with email. You'll learn how to write algorithms that automatically sort and redirect email based on statistical patterns. Authors Drew Conway and John Myles White approach the process in a practical fashion, using a case-study driven approach rather than a traditional math-heavy presentation.

This book also includes a short tutorial on using the popular R language to manipulate and analyze data. You'll get clear examples for analyzing sample data and writing machine learning programs with R.Mine email content with R functions, using a collection of sample filesAnalyze the data and use the results to write a Bayesian spam classifierRank email by importance, using factors such as thread activityUse your email ranking analysis to write a priority inbox programTest your classifier and priority inbox with a separate email sample set

Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data. With this book, you'll learn machine learning and statistics tools in a practical fashion, using black-box solutions and case studies instead of a traditional math-heavy presentation. By exploring each problem in this book in depth - including both viable and hopeless approaches - you'll learn to recognize when your situation closely matches traditional problems. Then you'll discover how to apply classical statistics tools to your problem. Machine Learning for Hackers is ideal for programmers from private, public, and academic sectors.