Böcker av Drew Conway

If youre an experienced programmer willing to crunch data, this concise guide will show you how to use machine learning to work with email. Youll 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. Youll 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

If youre an experienced programmer interested in crunching data, this book will get you started with machine learninga toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, youll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.Develop a nave Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a whom to follow recommendation system from Twitter data