Sucar, Luis Enrique
Probabilistic Graphical Models: Principles and Applications (Advances in Computer Vision and Pattern Recognition)
- ISBN 13:
- 9783030619428
- author:
- Sucar, Luis Enrique
- format:
- Hardback
- publisher:
- Springer Nature Switzerland AG
- language:
- English
- Publication Year:
- 2020
- Pages:
- 350
- Dimensions:
- 23.4 x 15.6 x 2.2 centimeters (0
- Genre:
- Computers, Computer Science, Computers,
- Condition:
- New
- Availability:
- Item usually sent within 5 working days
Description
Probabilistic Graphical Models: A Comprehensive Introduction This updated edition provides a general introduction to probabilistic graphical models from an engineering perspective. It covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles. The book reviews real-world applications for each type of model, drawn from various disciplines, such as Bayesian classifiers, hidden Markov models, and Bayesian networks. New material includes partially observable Markov decision processes, causal graphical models, and deep learning, with a software library for several graphical models in Python. With its broad range of topics and practical examples, this textbook/reference is suitable for those looking to understand the principles and applications of probabilistic graphical models.
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