Machine Learning for Hackers

作 者:
Drew Conway, John Myles White
日 期:
2011年12月
ISBN:
1449303714

简介

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 naïve Bayesian classifier to determine if an email is spam, based only on its text
  • Use linear regression to predict the number of page views for the top 1,000 websites
  • Learn optimization techniques by attempting to break a simple letter cipher
  • Compare and contrast U.S. Senators statistically, based on their voting records
  • Build a “whom to follow” recommendation system from Twitter data

下载

公众号订阅号
请扫描二维码进入公众号发送消息 geekgist 获取提取码

消息“GeekGist”不区分大小写,提取码有效期为一个月左右,输入后会自动存储在本地,下次无需重复输入。