Learning Bayesian Networks Book

Learning Bayesian Networks, Learning Bayesian Networks offers the first accessible and unified text on the study and application of Bayesian networks. This book serves as a key textbook or reference for anyone with an interest in probabilistic modeling in the fields of comput, Learning Bayesian Networks

4 out of 5 stars based on 2 reviews

Learning Bayesian Networks
Written by author Richard E. Neapolitan
Published by Prentice Hall, March 2003
Learning Bayesian Networks offers the first accessible and unified text on the study and application of Bayesian networks. This book serves as a key textbook or reference for anyone with an interest in probabilistic modeling in the fields of comput
In this first edition book, methods are discussed for doing inference in Bayesian networks and inference diagrams. Hundreds of examples and problems allow readers to grasp the information.Some of the topics discussed include Pearl's message passing alg

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Book Categories

Authors

Preface
I Basics
1 Introduction to Bayesian Networks 1
2 More DAG/Probability Relationships 69
II Inference
3 Inference: Discrete Variables 125
4 More Inference Algorithms 183
5 Influence Diagrams 233
III Learning
6 Parameter Learning: Binary Variables 285
7 More Parameter Learning 373
8 Bayesian Structure Learning 433
9 Approximate Bayesian Structure Learning 503
10 Constraint-Based Learning 533
11 More Structure Learning 609
IV Applications
12 Applications 639
Bibliography 647
Index 667

Title: Learning Bayesian Networks

Manufacturer:

Prentice Hall

Item Number: 9780130125347

Publication Date: March 2003

Number: 2

Product Description: Learning Bayesian Networks

Universal Product Code (UPC): 9780130125347

WonderClub Stock Keeping Unit (WSKU): 9780130125347

Rating: 4/5 based on 2 Reviews

Image Location: https://wonderclub.com/images/covers/53/47/9780130125347.jpg

Category: Media >> Books

Weight: 0.200 kg (0.44 lbs)

Width: 7.000 cm (2.76 inches)

Heigh : 9.100 cm (3.58 inches)

Depth: 1.600 cm (0.63 inches)

Date Added: August 25, 2020, Added By: Ross

Date Last Edited: August 25, 2020, Edited By: Ross

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$110.01	Digital	Arrives between May 4 - Jun 3 Login to your account for a direct download. Some files are emailed from Dropbox. Continent $0.00 - World $0.00	WonderClub (9296 total ratings)

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Simon Phillips

reviewed Learning Bayesian Networks on February 09, 2017

Learning Bayesian Networks

For those who are interested in machine learning.

very technical introductions, but not totally unapproachable. the content is more like a collection of papers about certain topics, and very comprehensive at it too.

feel free to jump from a chapter to another, or skip some chapters, there's no continuation between chapters anyway.

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Learning Bayesian Networks, <i>Learning Bayesian Networks</i> offers the first accessible and unified text on the study and application of Bayesian networks. This book serves as a key textbook or reference for anyone with an interest in probabilistic modeling in the fields of comput, Learning Bayesian Networks

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Add Learning Bayesian Networks, Learning Bayesian Networks offers the first accessible and unified text on the study and application of Bayesian networks. This book serves as a key textbook or reference for anyone with an interest in probabilistic modeling in the fields of comput, Learning Bayesian Networks to your collection on WonderClub

Learning Bayesian Networks Book

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	Preface
I	Basics
1	Introduction to Bayesian Networks	1
2	More DAG/Probability Relationships	69
II	Inference
3	Inference: Discrete Variables	125
4	More Inference Algorithms	183
5	Influence Diagrams	233
III	Learning
6	Parameter Learning: Binary Variables	285
7	More Parameter Learning	373
8	Bayesian Structure Learning	433
9	Approximate Bayesian Structure Learning	503
10	Constraint-Based Learning	533
11	More Structure Learning	609
IV	Applications
12	Applications	639
	Bibliography	647
	Index	667