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Machine Learning for Hackers: Case Studies and Algorithms to Get You Started Paperback – 2012 by Drew Conway (Author), John Myles (Author)

If youíre an experienced programmer interested in crunching data, this book will get you started with machine learningóa 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, youíll 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 naÔve 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 ìwhom to followî recommendation system from Twitter data 

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Machine Learning for Hackers: Case Studies and Algorithms to Get You Started Paperback – 2012 by Drew Conway (Author), John Myles (Author) 
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Machine Learning for Hackers: Case Studies and Algorithms to Get You Started Paperback – 2012 by Drew Conway (Author), John Myles (Author) 


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