Probabilistic Graphical Models: Principles and Techniques

Most tasks require a person or an automated system to reason—to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used...

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Book Details

Filename Hy0iWF_unUW.pdf
Filetype PDF
Filesize 31.25 MB
ISBN 0 /
Pages 1280 pages

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