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.