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Probabilistic Machine Learning: Advanced Topics (Adaptive Computation and Machine Learning series) - Hardcover
Synopsis
An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.
An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts...
About the Author
Kevin P. Murphy is a Research Scientist at Google in Mountain View, California, where he works on artificial intelligence, machine learning, and Bayesian modeling.
"About this title" may belong to another edition of this title.
- PublisherThe MIT Press
- Publication date2023
- ISBN 10 0262048434
- ISBN 13 9780262048439
- BindingHardcover
- LanguageEnglish
- Number of pages1360
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Probabilistic Machine Learning: Advanced Topics (Adaptive Computation and Machine Learning series)
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