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Synopsis
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. The second edition of Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. In order to present a unified treatment of machine learning problems and solutions, it discusses many methods from different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining. All learning algorithms are explained so that the student can easily move from the equations in the book to a computer program. The text covers such topi
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About the Author
Ethem Alpaydin is a Professor in the Department of Computer Engineering at Bogaziçi University, Istanbul.
Review
"A few years ago, I used the first edition of this book as a reference book for a project I was working on. The clarity of the writing, as well as the excellent structure and scope, impressed me. I am more than pleased to find that this second edition continues to be highly informative and comprehensive, as well as easy to read and follow." Radu State Computing Reviews
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- PublisherMit Pr
- Publication date2010
- ISBN 10 026201243X
- ISBN 13 9780262012430
- BindingHardcover
- LanguageEnglish
- Edition number2
- Number of pages537
- Rating
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