Elements of Machine Learning
Language: English
Published by Morgan Kaufmann, 1995
- Hardcover
- Used
Seller: Phatpocket Limited, Waltham Abbey, HERTS, United KingdomPhatpocket Limited
AbeBooks seller since April 28, 2005
Condition: Used - Good
US$ 24.51
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Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
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- Title
- Elements of Machine Learning
- Author
- Langley, Pat
- Publisher
- Morgan Kaufmann
- Publication year
- 1995
- Condition
- Good
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1558603018
- ISBN 13
- 9781558603011
Recent years have seen an explosion of work on machine learning, the computational study of algorithms that improve performance based on experience. Research on rule induction, neural networks, genetic algorithms, case-based reasoning, and probabilistic inference has produced a variety of robust methods for inducing knowledge from training data. This book covers the main induction algorithms explored in the literature and presents them within a coherent theoretical framework that moves beyond traditional paradigm boundaries.
Elements of Machine Learning provides a comprehensive introduction to the fundamental concepts and problems in the field. The book illustrates a variety of basic algorithms for inducing simple concepts from experience, presents alternatives for organizing learned concepts into large-scale structures, and discusses adaptations of the learning methods to more complex problem-solving tasks. The chapters describe these computational techniques in detail and give examples of their operation, along with exercises and references to the literature.
This text is suitable for use in graduate courses on machine learning. Researchers and students in artificial intelligence, cognitive science, and statistics will find it a useful and informative addition to their libraries.
"Synopsis" may belong to another edition of this title.
From the Back Cover
Recent years have seen an explosion of work on machine learning, the computational study of algorithms that improve performance based on experience. Research on rule induction, neural networks, genetic algorithms, case-based reasoning, and probabilistic inference has produced a variety of robust methods for inducing knowledge from training data. This book covers the main induction algorithms explored in the literature and presents them within a coherent theoretical framework that moves beyond traditional paradigm boundaries.
Elements of Machine Learning provides a comprehensive introduction to the fundamental concepts and problems in the field. The book illustrates a variety of basic algorithms for inducing simple concepts from experience, presents alternatives for organizing learned concepts into large-scale structures, and discusses adaptations of the learning methods to more complex problem-solving tasks. The chapters describe these computational techniques in detail and give examples of their operation, along with exercises and references to the literature.
This text is suitable for use in graduate courses on machine learning. Researchers and students in artificial intelligence, cognitive science, and statistics will find it a useful and informative addition to their libraries.
"About the title" may belong to another edition of this title.
Phatpocket Limited
Waltham Abbey, HERTS, United Kingdom
AbeBooks seller since April 28, 2005
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Phatpocket Limited is a world class secondhand bookstore located in the Hertfordshire countryside in the United Kingdom. We specialize in textbooks across an enormous variety of subjects. We aim to provide a low cost source of high quality textbooks to the academic community. We also have a sizable collection of rare and collectible books. We are dedicated to providing our customers with the highest standard of customer service in the bookselling business.Phatpocket Limited is registered in England and Wales: No. 04924751.…
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