Download the fantastic book titled Machine Learning for Hackers written by Drew Conway, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Machine Learning for Hackers", which was released on 13 February 2012. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.
Summary of Machine Learning for Hackers by Drew Conway PDF
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
Detail About Machine Learning for Hackers PDF
- Author : Drew Conway
- Publisher : "O'Reilly Media, Inc."
- Genre : Computers
- Total Pages : 324 pages
- ISBN : 1449330533
- Release Date : 13 February 2012
- PDF File Size : 34,5 Mb
- Language : English
- Rating : 4.5/5 from 7 reviews
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