Machine Learning for Hackers

Case Studies and Algorithms to Get You Started

Nonfiction, Computers, Advanced Computing, Natural Language Processing, Theory, Programming
Cover of the book Machine Learning for Hackers by Drew Conway, John Myles White, O'Reilly Media
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Author: Drew Conway, John Myles White ISBN: 9781449330538
Publisher: O'Reilly Media Publication: February 13, 2012
Imprint: O'Reilly Media Language: English
Author: Drew Conway, John Myles White
ISBN: 9781449330538
Publisher: O'Reilly Media
Publication: February 13, 2012
Imprint: O'Reilly Media
Language: English

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
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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