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Learning Bayesian Networks by Richard E. Neapolitan (Paperback, 2003)

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Learning Bayesian Networks offers the first accessible and unified text on the study and application of Bayesian networks. This book serves as a key textbook or reference for anyone with an interest in probabilistic modeling in the fields of computer science, computer engineering, and electrical engineering. This text is also a valuable supplemental resource for courses on expert systems, machine learning, and artificial intelligence. Appropriate for classroom teaching or self-instruction, the text is organized to provide fundamental concepts in an accessible, practical format. Beginning with a basic theoretical introduction, the author then provides a comprehensive discussion of inference, methods of learning, and applications based on Bayesian networks and beyond. Learning Bayesian Networks: *Includes hundreds of examples and problems *Makes learning easy by introducing complex concepts through simple examples *Clarifies with separate discussions on statistical development of Bayesian networks and application to causality