- Paperback: 324 pages
- Publisher: O'Reilly; 1st edition (February 25, 2012)
- Language: English
- ISBN-10: 1449303714
- ISBN-13: 978-1449303716
- Product Dimensions: 7 x 0.8 x 9.2 inches
- Shipping Weight: 1.4 pounds (View shipping rates and policies)
- Average Customer Review: 30 customer reviews
- Amazon Best Sellers Rank: #794,078 in Books (See Top 100 in Books)
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Machine Learning for Hackers: Case Studies and Algorithms to Get You Started 1st Edition
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The Amazon Book Review
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About the Author
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.
Top customer reviews
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Not really for hackers but those who want to learn and use R better.
I liked it but it did not help me much with machine learning.
There is way too much time spent on R, dedicated to such things as parsing email messages, and spidering webpages, etc. These are things that no-one with other tools available would do in R. And it's not that it's easier to do it in R, it's actually harder than using an appropriate library, like JavaMail. And yet, while much time is spent in details, like regexes to extract dates (ick!), more interesting R functions are given short shrift.
There's some good material in here, but it's buried under the weight of doing everything in R. If you are a non-programmer, and want to use only one hammer for everything, then R is not a bad choice. But it's not a good choice for developers that are already comfortable with a wider variety of tools.
I'd recommend Programming Collective Intelligence by Segaran, if you would describe yourself as a "Hacker".
The text is parsimonious.
The examples are interesting.
The coding is clever.
The book is less expensive and easier to understand than most Springer texts.
A substantial part of the code is peripheral tasks; this can be skipped.
Some of the code is out of date.
These Con's are trivial. The book is great. I would buy any other books written by these authors.