David Bellot - Learning Probabilistic Graphical Models in R.pdf

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Learning Probabilistic Graphical

Models in R

Familiarize yourself with probabilistic graphical models

through real-world problems and illustrative code

examples in R

David Bellot

BIRMINGHAM - MUMBAI

Learning Probabilistic Graphical Models in R

system, or transmitted in any form or by any means, without the prior written

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critical articles or reviews.

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of the information presented. However, the information contained in this book is

sold without warranty, either express or implied. Neither the author, nor Packt

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However, Packt Publishing cannot guarantee the accuracy of this information.

First published: April 2016

Production reference: 1270416

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78439-205-5

www.packtpub.com

Credits

Author

David Bellot

Reviewers

Mzabalazo Z. Ngwenya

Prabhanjan Tattar

Indexer

Acquisition Editor

Divya Poojari

Graphics

Content Development Editor

Trusha Shriyan

Production Coordinator

Technical Editor

Vivek Arora

Cover Work

Copy Editor

Stephen Copestake

Nilesh Mohite

Abhinash Sahu

Mariammal Chettiyar

Project Coordinator

Kinjal Bari

Proofreader

Safis Editing

About the Author

David Bellot

is a PhD graduate in computer science from INRIA, France, with a

focus on Bayesian machine learning. He was a postdoctoral fellow at the University

of California, Berkeley, and worked for companies such as Intel, Orange, and

Barclays Bank. He currently works in the financial industry, where he develops

financial market prediction algorithms using machine learning. He is also a

contributor to open source projects such as the Boost C++ library.

David Bellot - Learning Probabilistic Graphical Models in R.pdf

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