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Probabilistic Graphical Models: Principles and Techniques Adaptive Computation and Machine Learning series 1st Edition

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SKU: PROB

$89.00

 The MIT Press

 New

 978-0262013192

 by Nir Friedman

 Hardcover

10 in stock

Description

Most jobs need reasoning—drawing conclusions based on available data—by a person or an automated system. This book’s framework of probabilistic graphical models provides a generic approach to this problem. The method is model-based, allowing for the creation of interpretable models that may then be changed by reasoning algorithms. These models can also be trained automatically from data, which means they can be utilised in situations when manually building a model is difficult or impossible. Because uncertainty is an unavoidable part of most real-world applications, the book focuses on probabilistic models, which make uncertainty explicit and enable more accurate models.

Additional information

Condition

New

ISBN- 13

978-0262013192

ISBN - 10

262013193

Edition

1st

Publisher

The MIT Press

Format

Hardcover

Dimension

9.22 x 8.18 x 2.05 inches

Item Weight

4.63 pounds

Pages

1231

3 reviews for Probabilistic Graphical Models: Principles and Techniques Adaptive Computation and Machine Learning series 1st Edition

  1. Cannon Gray LLC

    Excellent self study book for probabilistic graphical models.

  2. Delip

    If you want a very close look under the hood of Bayesian Networks, I can highly recommend Probabilistic Graphical Models.

  3. Rao

    I have read this book in bits and pieces and find it extremely useful.

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