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Synopsis
A coherent introduction to core concepts and deep learning techniques that are critical to academic research and real-world applications.
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About the Author
Hui Jiang is Professor of Electrical Engineering and Computer Science at York University, where he has been since 2002. His main research interests include machine learning, particularly deep learning, and its applications to speech and audio processing, natural language processing, and computer vision. Over the past 30 years, he has worked on a wide range of research problems from these areas and published hundreds of technical articles and papers in the mainstream journals and top-tier conferences. His works have won the prestigious IEEE Best Paper Award and the ACL Outstanding Paper honor.
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Machine Learning Fundamentals
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Cambridge University Press (edition New), 2022
ISBN 10: 1108940021
ISBN 13: 9781108940023
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MACHINE LEARNING FUNDAMENTALS
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Machine Learning Fundamentals : A Concise Introduction
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ISBN 10: 1108940021
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Machine Learning Fundamentals
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Machine Learning Fundamentals
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Machine Learning Fundamentals: A Concise Introduction
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Cambridge University Press 2021-11-25, 2021
ISBN 10: 1108940021
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Machine Learning Fundamentals: A Concise Introduction
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Machine Learning Fundamentals (Paperback)
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Cambridge University Press, Cambridge, 2021
ISBN 10: 1108940021
ISBN 13: 9781108940023
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Paperback. Condition: new. Paperback. This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely from scratch based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts. This lucid and coherent introduction to supervised machine learning presents core concepts in a concise, logical and easy-to-follow way for readers with some mathematical preparation but no prior exposure to machine learning. Coverage includes widely used traditional methods plus recently popular deep learning methods. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781108940023
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Machine Learning Fundamentals : A Concise Introduction
Published by
Cambridge University Press, 2022
ISBN 10: 1108940021
ISBN 13: 9781108940023
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Machine Learning Fundamentals: A Concise Introduction
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Cambridge University Press, 2021
ISBN 10: 1108940021
ISBN 13: 9781108940023
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Paperback. Condition: Brand New. 400 pages. 10.00x8.00x1.00 inches. In Stock. Seller Inventory # __1108940021
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