MACHINE LEARNING
The Art and Science of Algorithms
that Make Sense of Data
As one of the most comprehensive machine learning texts around, this book does
justice to the field’s incredible richness, but without losing sight of the unifying
principles.
Peter Flach’s clear, example-based approach begins by discussing how a spam
filter works, which gives an immediate introduction to machine learning in action,
with a minimum of technical fuss. He covers a wide range of logical, geometric
and statistical models, and state-of-the-art topics such as matrix factorisation and
ROC analysis. Particular attention is paid to the central role played by features.
Machine Learningwill set a new standard as an introductory textbook:
The Prologue and Chapter 1 are freely available on-line, providing an accessible
first step into machine learning.
The use of established terminology is balanced with the introduction of new and
useful concepts.
Well-chosen examples and illustrations form an integral part of the text.
Boxes summarise relevant background material and provide pointers for revision.
Each chapter concludes with a summary and suggestions for further reading.
A list of ‘Important points to remember’ is included at the back of the book
together with an extensive index to help readers navigate through the material.
MACHINE LEARNING
The Art and Science of Algorithms
that Make Sense of Data
PETER FLACH
cambridge university press
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Singapore, S˜ao Paulo, Delhi, Mexico City
Cambridge University Press
The Edinburgh Building, Cambridge CB2 8RU, UK
Published in the United States of America by Cambridge University Press, New York
www.cambridge.org
Informationonthistitle:www.cambridge.org/9781107096394
CPeter Flach 2012
This publication is in copyright. Subject to statutory exception
and to the provisions of relevant collective licensing agreements,
no reproduction of any part may take place without the written
permission of Cambridg
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