A Concise Introduction to Machine Learning

✍ Scribed by A.C. Faul (Author)

Publisher: Chapman and Hall/CRC
Year: 2019
Leaves: 335
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

The emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms are often taught side by side without showing the similarities and differences between them. This book addresses the commonalities, and aims to give a thorough and in-depth treatment and develop intuition, while remaining concise.

This useful reference should be an essential on the bookshelves of anyone employing machine learning techniques.

The author`s webpage for the book can be accessed here.

✦ 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

✦ Subjects

Computer Science;Artificial Intelligence;Machine Learning - Design;Neural Networks;Databases;Data Preparation & Mining;Engineering & Technology;Systems & Control Engineering;Machine Learning;Mathematics & Statistics;Statistics & Probability;Statistics;Statistical Computing

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