Editorial ReviewsReview"This elegant book covers both rigorous theory and practical methods of machine learning. This makes it a rather unique resource, ideal for all those who want to understand how to find structure in data."
Bernhard Schölkopf, Max Planck Institute for Intelligent Systems
"This is a timely text on the mathematical foundations of machine learning, providing a treatment that is both deep and broad, not only rigorous but also with intuition and insight. It presents a wide range of classic, fundamental algorithmic and analysis techniques as well as cutting-edge research directions. This is a great book for anyone interested in the mathematical and computational underpinnings of this important and fascinating field."
Avrim Blum, Carnegie Mellon University
Book DescriptionMachine learning makes use of computer programs to discover meaningful patters in complex data. It is one of the fastest growing areas of computer science, with far-reaching applications. This book explains the principles behind the automated learning approach and the considerations underlying its usage. The authors explain the "hows" and "whys" of the most important machine-learning algorithms, as well as their inherent strengths and weaknesses, making the field accessible to students and practitioners in computer science, statistics, and engineering.
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