Machine Learning Fundamentals: A Concise Introduction

Jiang, Hui

ISBN 10: 1108837042 ISBN 13: 9781108837040

Editorial: Cambridge University Press, 2022

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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.

Acerca del autor: 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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T�tulo: Machine Learning Fundamentals: A Concise ...
Editorial: Cambridge University Press
A�o de publicaci�n: 2022
Encuadernaci�n: Encuadernaci�n de tapa dura
Condici�n: New

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Jiang, Hui

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Jiang, Hui

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Hui Jiang

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Jiang, Hui

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Jiang, Hui

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Condici�n: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 t. N� de ref. del art�culo: 497289512

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Machine Learning Fundamentals : A Concise Introduction

Jiang, Hui

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Machine Learning Fundamentals: A Concise Introduction

Hui Jiang

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ISBN 10: 1108837042 ISBN 13: 9781108837040

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Machine Learning Fundamentals (Hardcover)

Hui Jiang

Publicado por Cambridge University Press, Cambridge, 2021

ISBN 10: 1108837042 ISBN 13: 9781108837040

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Hardcover. Condici�n: new. Hardcover. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de ref. del art�culo: 9781108837040

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