Machine Learning Fundamentals

A Concise Introduction

Machine Learning Fundamentals
Hui Jiang
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NZ$ 82.95
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NZ$ 74.65
Paperback
h253 x 204mm - 418pg
25 Nov 2021 UK
International import eta 7-19 days
9781108940023
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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.
' Dr Jiang has done a superb job in covering many methods, both theoretical and practical, across a broad spectrum of machine learning in this timely book. I worked closely with Dr Jiang on Bayesian speech recognition during late 90' s and I have personally witnessed his excellent skills in applying machine learning to solving a wide range of practical problems. In this book, Dr Jiang has expanded his scope into a much wider set of logically organized topics in modern machine learning. The organization of the material is highly unique and cogent. A number of hot topics in machine learning, including deep learning and neural networks, are naturally incorporated in the book, which not only provides sufficient technical depth for the readers but also aligns well with popular toolkits for implementing the related machine learning methods. ' Li Deng, formerly of Microsoft Corporation and Citadel LLC ' It is beautifully designed, with many color images that make the complex subject matter manageable . . . It is a book for students and developers who are committed to specializing in ML or a specific area of it. ' Karl van Heijster , De Leesclub van Alles
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.
Status: Active
ISBN-13: 9781108940023
Published: 25 Nov 2021
Published In: United Kingdom
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Format: Paperback
Height: 253mm
Width: 204mm
Spine: 24mm
Weight: 910g
Pages: 418

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