Machine Learning for Hackers

书名：Machine Learning for HackersCaseStudiesandAlgorithmstoGetYouStarted
作者：DrewConway/JohnMylesWhite
译者：
ISBN：9781449303716
出版社：O'ReillyMedia
出版时间：2012-2-22
格式：epub/mobi/azw3/pdf
页数：324
豆瓣评分： 7.3

书籍简介：

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

作者简介：

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.

John Myles White is a PhD candidate in Psychology at Princeton. He studies pattern recognition, decision-making, and economic behavior using behavioral methods and fMRI. He is particularly interested in anomalies of value assessment.

书友短评：

@ 喵喵喵 適合本行不是計算機的人。 @ FantasyDJ 被名字吸引过去了，看了前三章，书中完全就是解释他们写过的R程序，学着稀里糊涂的，反正我是没兴趣继续看下去了。他们的R语言代码还是有值得借鉴的地方，应该适合有点R语言基础的人去学习。 @ ET民工 读了中文版的书，现在好像应该用pyro更好一些吧？ @ 蝉 :无 @ thali110 data processing part可以看看 至于machine learning连个入门都嫌浅 @ ET民工 读了中文版的书，现在好像应该用pyro更好一些吧？ @ 豆友81016514 好书 R语言细节很丰富 case-based很适合熟悉算法 @ onnekas 不错的入门书，有些code已经过时 @ 胡大善人 对于曾经的我，这本苏帮助还是挺大的。不过，仅此而已了。 @ 萨利 跟machine learning没多大关系 属于data prepossessing吧 一般

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