Machine Learning Basics

This lecture covers the general organization of the course, including the schedule, grading, and main references. It introduces the basics of machine learning, such as supervised and unsupervised learning, linear regression, and the concepts of training and testing models. The lecture also delves into the understanding of data, data sets vs. data samples, and the insights gained from different types of data. Practical examples and exercises are provided to illustrate key concepts.