Machine Learning: An Algorithmic Perspective (Second edition)
Language: English
Published by CRC Press | Taylor & Francis Group, Boca Raton, FL, 2015
Series: Book 6 of 15 - Chapman & Hall/Crc Machine Learning & Pattern Recognition
- Hardcover
- Used
Seller: Twice Sold Tales, Capitol Hill, Seattle, WA, U.S.A.Twice Sold Tales, Capitol Hill
AbeBooks seller since August 31, 1999
Condition: Used - Very good
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- Title
- Machine Learning: An Algorithmic Perspective (Second edition)
- Author
- Marsland, Stephen
- Publisher
- CRC Press | Taylor & Francis Group, Boca Raton, FL
- Publication year
- 2015
- Condition
- Very good
- Binding
- Hardcover, 437 pages
- Language
- English
- ISBN 10
- 1466583282
- ISBN 13
- 9781466583283
- Edition
- 2nd Edition
- Series
- Book 6 of 15: Chapman & Hall/Crc Machine Learning & Pattern Recognition
- Seller catalogs
- Science
A Proven, Hands-On Approach for Students without a Strong Statistical Foundation
Since the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students without a strong statistical background often find it hard to get started in this area.
Remedying this deficiency, Machine Learning: An Algorithmic Perspective, Second Edition helps students understand the algorithms of machine learning. It puts them on a path toward mastering the relevant mathematics and statistics as well as the necessary programming and experimentation.
New to the Second Edition
- Two new chapters on deep belief networks and Gaussian processes
- Reorganization of the chapters to make a more natural flow of content
- Revision of the support vector machine material, including a simple implementation for experiments
- New material on random forests, the perceptron convergence theorem, accuracy methods, and conjugate gradient optimization for the multi-layer perceptron
- Additional discussions of the Kalman and particle filters
- Improved code, including better use of naming conventions in Python
Suitable for both an introductory one-semester course and more advanced courses, the text strongly encourages students to practice with the code. Each chapter includes detailed examples along with further reading and problems. All of the code used to create the examples is available on the author’s website.
"Synopsis" may belong to another edition of this title.
About the Author
Stephen Marsland is a professor of scientific computing and the postgraduate director of the School of Engineering and Advanced Technology (SEAT) at Massey University. His research interests in mathematical computing include shape spaces, Euler equations, machine learning, and algorithms. He received a PhD from Manchester University
"About the title" may belong to another edition of this title.
Twice Sold Tales, Capitol Hill
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