Description
From Book News, Inc. An introductory text on primary approaches to machine learning and
the study of computer algorithms that improve automatically through experience. Introduce
basics concepts from statistics, artificial intelligence, information theory, and other disciplines as
need arises, with balanced coverage of theory and practice, and presents major algorithms with
illustrations of their use. Includes chapter exercises. Online data sets and implementations of
several algorithms are available on a Web site. No prior background in artificial intelligence or
statistics is assumed. For advanced undergraduates and graduate students in computer science,
engineering, statistics, and social sciences, as well as software professionals. Book News, Inc.®,
Portland, OR
Book Info: Presents the key algorithms and theory that form the core of machine learning.
Discusses such theoretical issues as How does learning performance vary with the number of
training examples presented? and Which learning algorithms are most appropriate for various
types of learning tasks? DLC: Computer algorithms.
Book Description: This book covers the field of machine learning, which is the study of
algorithms that allow computer programs to automatically improve through experience. The
book is intended to support upper level undergraduate and introductory level graduate courses in
machine learning
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