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Machine Learning for Hackers: Case Studies and Algorithms to Get You Started

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Machine Learning for Hackers: Case Studies and Algorithms to Get You Started

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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

Publisher	O'Reilly
Publication date	March 20, 2012
Edition	First Edition
Language	English
Print length	320 pages
ISBN-10	1449303714
ISBN-13	978-1449303716
Item Weight	1.14 pounds (520 grams)
Dimensions	7 x 0.75 x 9.19 inches (17.8 x 1.9 x 23.3 cm)

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Machine Learning for Hackers: Case Studies and Algorithms to Get You Started

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Tambaya: Yadda ake Siyayya Machine Learning for Hackers: Case Studies and Kan layi Daga Ubuy?

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Amsa: Ee, a Ubuy Niger wannan samfurin yana samuwa gare ku don siyayya akan farashi mai ma'ana.. Ba a samun Machine Learning for Hackers: Case Studies and a cikin gida amma kuna iya amincewa da mu da ayyukan jigilar mu na yau da kullun.
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Amsa: Lokacin isar da samfurin da aka umarce ku ya bambanta gwargwadon abin da kuka yi oda da hanyar jigilar kaya da kuka zaɓa.. An ambaci lokacin isar da kiyasin yayin aiwatar da biyan kuɗi, don haka a kula yayin sayayya.

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Machine Learning for Hackers: Case Studies and Algorithms to Get You Started