A Concise Introduction to Machine Learning: 1st Edition (Paperback) book cover

A Concise Introduction to Machine Learning

1st Edition

By A.C. Faul

Chapman and Hall/CRC

314 pages | 123 B/W Illus.

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Paperback: 9780815384106
pub: 2019-08-12
Available for pre-order
$59.95
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Hardback: 9780815384205
pub: 2019-08-12
Available for pre-order
$159.95
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Description

Machine Learning is known by many different names, and is used in many areas of science. It is also used for a variety of applications, including spam filtering, optical character recognition, search engines, computer vision, NLP, advertising, fraud detection, robotics, data prediction, astronomy. Considering this, it can often be difficult to find a solution to a problem in the literature, simply because different words and phrases are used for the same concept. This class-tested textbook aims to alleviate this, using mathematics as the common language. It covers a variety of machine learning concepts from basic principles, and llustrates every concept using examples in MATLAB.

Table of Contents

Chapter 1. Introduction

Chapter 2. Probability Theory

Chapter 3. Sampling

Chapter 4. Linear Classification

Chapter 5. Non-Linear Classification

Chapter 6. Dimensionality Reduction

Chapter 7. Regression

Chapter 8. Feature Learning

About the Author

Anita Faul is a teaching associate and Fellow, Director of Studies in Mathematics and Graduate Tutor at Selwyn College.

About the Series

Chapman & Hall/CRC Machine Learning & Pattern Recognition

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Subject Categories

BISAC Subject Codes/Headings:
BUS061000
BUSINESS & ECONOMICS / Statistics
COM000000
COMPUTERS / General
COM012040
COMPUTERS / Programming / Games
COM021030
COMPUTERS / Database Management / Data Mining
COM037000
COMPUTERS / Machine Theory
SCI055000
SCIENCE / Physics