Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)

(Part of the Adaptive Computation and Machine Learning Series)

by Daphne Koller, N. Friedman, Nir Friedman

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Book Overview

A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.Most tasks require a person or an... This description may be from another edition of this product.

Format:Hardcover

Language:English

ISBN:0262013193

Release Date:July 2009

Publisher:The MIT Press

Length:1231 Pages

Weight:4.80 lbs.

Dimensions:2.0" x 8.2" x 9.2"

Related Subjects

Computers Computers & Technology Human Vision & Language Systems Industrial, Manufacturing & Operational Systems Math Mathematics Natural Language Processing Pattern Recognition Probability & Statistics Science & Math

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Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)

(Part of the Adaptive Computation and Machine Learning Series)

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