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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.
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Introduction to Machine Learning (Adaptive Computation and Machine Learning series)
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Introduction to Machine Learning
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Introduction to Machine Learning
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Introduction to Machine Learning
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Introduction to Machine Learning
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Introduction to Machine Learning
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Introduction to Machine Learning
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Introduction to Machine Learning (Adaptive Computation and Machine Learning series)
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Introduction to Machine Learning
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Introduction to Machine Learning (2nd edition)
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