01·Definition and applications of ML

Introduction

What exactly is machine learning, and how does it differ from classical programming? We rely on Tom Mitchell's (1997) operational definition: a program learns from experience E with respect to tasks T and a performance measure P if its performance on T as measured by P improves with E. This lesson distinguishes ML from AI and Deep Learning, discusses real applications (recommendations, NLP, computer vision, churn prediction), and shows when ML is the right tool versus when rules are still better.