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Bayesian Reasoning and Machine Learning Hardback de Barber
Descripción - Críticas 'This book is an exciting addition to the literature on machine learning and graphical models. What makes it unique and interesting is that it provides a unified treatment of machine learning and related fields through graphical models, a framework of growing importance and popularity. Another feature of this book lies in its smooth transition from traditional artificial intelligence to modern machine learning. The book is well-written and truly pleasant to read. I believe that it will appeal to students and researchers with or without a solid mathematical background.' Zheng-Hua Tan, Aalborg University, Denmark'With approachable text, examples, exercises, guidelines for teachers, a MATLAB toolbox and an accompanying website, Bayesian Reasoning and Machine Learning by David Barber provides everything needed for your machine learning course. Only students not included.' Jaakko Hollmén, Aalto University'The chapters on graphical models form one of the clearest and most concise presentations I have seen … The exposition throughout uses numerous diagrams and examples, and the book comes with an extensive software toolbox - these will be immensely helpful for students and educators. It's also a great resource for self-study.' Arindam Banerjee, University of Minnesota'I repeatedly get unsolicited comments from my students that the contents of this book have been very valuable in developing their understanding of machine learning … My students praise this book because it is both coherent and practical, and because it makes fewer assumptions regarding the reader's statistical knowledge and confidence than many books in the field.' Amos Storkey, University of Edinburgh Reseña del editor This practical introduction for final-year 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. Descripción del libro This practical introduction for final-year 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. Biografía del autor David Barber is Reader in Information Processing in the Department of Computer Science, University College London.
Detalles del Libro
- Name: Bayesian Reasoning and Machine Learning Hardback
- Autor: Barber
- Categoria: Libros,Ciencias, tecnología y medicina,Matemáticas
- Tamaño del archivo: 9 MB
- Tipos de archivo: PDF Document
- Idioma: Español
- Archivos de estado: AVAILABLE
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Bayesian Reasoning and Machine Learning ~ Bayesian reasoning and machine learning / David Barber. p. cm. Includes bibliographical references and index. ISBN 978-0-521-51814-7 1. Machine learning. 2. Bayesian statistical decision theory. I. Title. QA267.B347 2012 006.3 1 – dc23 2011035553 ISBN 978-0-521-51814-7 Hardback
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David Barber : Brml - Home Page browse ~ Bayesian Reasoning and Machine Learning. The book is available in hardcopy from Cambridge University Press. The publishers have kindly agreed to allow the online version to remain freely accessible. If you wish to cite the book, please use @BOOK{barberBRML2012, author = {Barber, D.}, title= {{Bayesian Reasoning and Machine Learning}},
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