Machine Learning Fundamentals: A Concise Introduction

Language: English

Published by Cambridge University Press, United Kingdom, Cambridge, 2021

1108940021 / 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. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Seller Inventory # GOR014173512

Title
Machine Learning Fundamentals: A Concise Introduction
Author
Hui Jiang (York University, Toronto)
Publisher
Cambridge University Press, United Kingdom, Cambridge
Publication year
2021
Condition
Very Good
Binding
Paperback
Language
English
ISBN 10
1108940021
ISBN 13
9781108940023
Item weight
903 grams
Dimensions
204.0 x 253.0

WorldofBooks

Goring-By-Sea, WS, United Kingdom

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