Machine Learning The Art and Science of Algorithms That Make Sense of Data

ISBN-10: 1107422221

ISBN-13: 9781107422223

Edition: 2012

Authors: Peter A. Flach
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Description: 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. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. 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. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

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Book details

List price: $55.00
Copyright year: 2012
Publisher: Cambridge University Press
Publication date: 9/20/2012
Binding: Paperback
Pages: 409
Size: 8.00" wide x 10.00" long x 1.00" tall
Weight: 2.002
Language: English

Prologue: a machine learning sampler
The ingredients of machine learning
Binary classification and related tasks
Beyond binary classification
Concept learning
Tree models
Rule models
Linear models
Distance-based models
Probabilistic models
Features
In brief: model ensembles
In brief: machine learning experiments
Epilogue: where to go from here
Important points to remember
Bibliography
Index
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