Machine Learning: An Applied Mathematics Introduction

✍ Scribed by Paul Wilmott

• Year: 2019
• Tongue: English
• Leaves: 246
• Category: Library

✦ Synopsis

Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the following topics - K Nearest Neighbours; K Means Clustering; Naïve Bayes Classifier; Regression Methods; Support Vector Machines; Self-Organizing Maps; Decision Trees; Neural Networks; Reinforcement Learning

✦ Table of Contents

Contents
Prologue
Chapter 1 - Introduction
Chapter 2 - General Matters
Chapter 3 - K Nearest Neighbours
Chapter 4 - K Means Clustering
Chapter 5 - Naive Bayes Classifier
Chapter 6 - Regression Methods
Chapter 7 - Support Vector Machines
Chapter 8 - Self-Organizing Maps
Chapter 9 - Decision Tree
Chapter 10 - Neural Networks
Chapter 11 - Reinforcement Learning
Datasets
Epilogue
Index