num_pages: 322
description: If you're an experienced programmer interested in crunching data this book will get you started with machine learning--a 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 you'll 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 naive 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 1000 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
language: None
title: Machine Learning for Hackers
publisher: O'Reilly