The Art of Machine Learning

CONTENTS IN DETAIL

ACKNOWLEDGMENTS

INTRODUCTION

0.1  What Is ML?

0.2  The Role of Math in ML Theory and Practice

0.3  Why Another ML Book?

0.4  Recurring Special Sections

0.5  Background Needed

0.6  The qe*-Series Software

0.7  The Book’s Grand Plan

0.8  One More Point

PART IPROLOGUE, AND NEIGHBORHOOD-BASED METHODS

1REGRESSION MODELS

1.1  Example: The Bike Sharing Dataset

1.1.1   Loading the Data

1.1.2   A Look Ahead

1.2  Machine Learning and Prediction

1.2.1   Predicting Past, Present, and Future

1.2.2   Statistics vs. Machine Learning in Prediction

1.3  Introducing the k-Nearest Neighbors Method

1.3.1   Predicting Bike Ridership with k-NN

1.4  Dummy Variables and Categorical Variables

1.5  Analysis with qeKNN()

1.5.1   Predicting Bike Ridership ...