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Empirical Approach to Machine Learning (Studies in Computational Intelligence #800) book cover by Plamen P. Angelov, Xiaowei Gu
Paperback

Empirical Approach to Machine Learning (Studies in Computational Intelligence #800)

by Plamen P. Angelov and Xiaowei Gu

From $175.99 / copy at 25+ copies; lower per-copy prices at higher quantities (see Volume pricing) As low as $171.99 at 100+

Total $4,399.75

Paperback · 423 pages Springer International Publishing · 2019

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About the book

Empirical Approach to Machine Learning (Studies in Computational Intelligence #800)

This book provides a ‘one-stop source’ for all readers who are interested in a new, empirical approach to machine learning that, unlike traditional methods, successfully addresses the demands of today’s data-driven world. After an introduction to the fundamentals, the book discusses in depth anomaly detection, data partitioning and clustering, as well as classification and predictors. It describes classifiers of zero and first order, and the new, highly efficient and transparent deep rule-based classifiers, particularly highlighting their applications to image processing. Local optimality and stability conditions for the methods presented are formally derived and stated, while the software is also provided as supplemental, open-source material. The book will greatly benefit postgraduate students, researchers and practitioners dealing with advanced data processing, applied mathematicians, software developers of agent-oriented systems, and developers of embedded and real-time systems. Itcan also be used as a textbook for postgraduate coursework; for this purpose, a standalone set of lecture notes and corresponding lab session notes are available on the same website as the code.

Dimitar Filev, Henry Ford Technical Fellow, Ford Motor Company, USA, and Member of the National Academy of Engineering, USA: “The book Empirical Approach to Machine Learning opens new horizons to automated and efficient data processing.”

Paul J. Werbos, Inventor of the back-propagation method, USA: “I owe great thanks to Professor Plamen Angelov for making this important material available to the community just as I see great practical needs for it, in the new area of making real sense of high-speed data from the brain.” 

Chin-Teng Lin, Distinguished Professor at University of Technology Sydney, Australia: “This new book will set up a milestone for the modern intelligent systems.”

Edward Tunstel, President of IEEE Systems, Man, Cybernetics Society, USA: “Empirical Approach to Machine Learning provides an insightful and visionary boost of progress in the evolution of computational learning capabilities yielding interpretable and transparent implementations.”


Details

Publisher
Springer International Publishing
Authors
Plamen P. Angelov, Xiaowei Gu
Format
Paperback
Published
Dec 10, 2019
ISBN-13
9783030132095
Pages
423
Printing
Printed on demand
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Empirical Approach to Machine Learning (Studies in Computational Intelligence #800) for groups: pricing

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CopiesPrice per copyYou save
25 – 49 $175.99 12% off list
50 – 99 $173.99 13% off list
100+ $171.99 14% off list
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Volume pricing applies automatically in your cart, with no code needed. Price per copy: 25 to 49 copies, $175.99 (12% off list); 50 to 99 copies, $173.99 (13% off list); 100+ copies, $171.99 (14% off list). Need a different quantity, or a quote to forward for approval? Ask a specialist and we will confirm pricing before you pay.

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