BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Bayesian Reasoning and Machine Learning

Bayesian Reasoning and Machine Learning

Bayesian Reasoning and Machine Learning Hardback - 2012

by Barber, David

Add to wish list
  • Used
  • Hardback

Description

ISBN: 9780521518147

CAMBRIDGE UNIVERSITY PRESS | 15 February 2019

Hardback | 735 pages 

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 hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year 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 problem-solving 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.

Ask the seller a question Add to wish list
A$77.85
A$77.85 Delivery to USA
Standard delivery: 14 to 21 days
More delivery options
Ships from Pentz Booksellers (South Africa)

Details

  • Title Bayesian Reasoning and Machine Learning
  • Author Barber, David
  • Binding Hardback
  • Edition International Ed
  • Pages 735
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press
  • Publication date 2012-02-02
  • Features Bibliography, Index, Table of Contents, Textbook
  • Bookseller's Inventory # 9780521518147
  • ISBN 9780521518147 / 0521518148
  • Weight 3.8 lbs (1.72 kg)
  • Dimensions 9.8 x 7.7 x 1.5 in (24.89 x 19.56 x 3.81 cm)
  • Category Computers - General Information
  • Library of Congress subjects Bayesian statistical decision theory, Machine learning
  • Library of Congress Catalogue Number 2011035553
  • Dewey Decimal Code 006.31
  • Quantity available 1

About Pentz Booksellers South Africa

Biblio member since 2021

Pentz Booksellers, founded in 1992 by Pentz, has expanded over the years and today carries more than 30 000 titles. The Campus Bookstore serves students, academics, universities and institutions with a wide range and in-depth assortment of general, academic, technical, professional and educational books. We also provide a wide variety of light reading and books that fit neither the academic nor mass-market mould.


Terms of Sale: 30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

If there are titles not listed, please feel free to contact us for requests as we do offer special orders.

Browse books from Pentz Booksellers

Reader reviews for Bayesian Reasoning and Machine Learning

From the publisher

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 hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year 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 problem-solving 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.
tracking-