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 Title: Bayesian Reasoning and Machine Learning
 Author(s) David Barber
 Publisher: Cambridge University Press (2012); eBook (Online Edition: David Barber ©2020)
 Permission: Online Edition Provided by the Author.
 Hardcover: 735 pages
 eBook: PDF (690 pages)
 Language: English
 ISBN10: 0521518148
 ISBN13: 9780521518147
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Book Description
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs.
This handson text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for finalyear undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models.
Students learn more than a menu of techniques, they develop analytical and problemsolving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.
This practical introduction for finalyear undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and linear algebra. Numerous examples and exercises are provided. Additional resources available online and in the comprehensive software package include computer code, demos and teaching materials for instructors.
About the Authors N/A
 Bayesian Thinking
 Deep Learning and Neural Networks
 Machine Learning
 Statistics, Mathematical Statistics
 Probability and Stochastic Processes
 Artificial Intelligence
 Bayesian Reasoning and Machine Learning (David Barber)
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