Empirical Approach to Machine Learning - Studies in Computational Intelligence 800 (Paperback)Plamen P. Angelov (author), Xiaowei Gu (author)
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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."
Publisher: Springer Nature Switzerland AG
Number of pages: 423
Weight: 694 g
Dimensions: 235 x 155 mm
Edition: Softcover reprint of the original 1st ed. 201
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