Chapter 1 Introduction

This is a set of notes for the Spring 2023 iteration of CS181: Machine Learning. CS 181 provides a broad and rigorous introduction to machine learning, probabilistic reasoning and decision-making in uncertain environments. We discuss the motivations behind common machine learning algorithms, and the properties that determine whether or not they will work well for a particular task. We derive the mathematical underpinnings for many common methods, as well as apply machine learning to challenges with real data. In doing so, students will gain a strong conceptual understanding of machine learning methods that can empower them to pursue future theoretical and practical directions.