Lecture
Introduction to Machine Learning: Basics and Examples
Description
This lecture provides an overview of the basics of machine learning, including supervised learning, reinforcement learning, density estimation, and dimension reduction. It covers the purpose, examples, and limits of machine learning, as well as different types of learning algorithms. The instructors, Michael Liebling and François Fleuret, explain the concepts through various examples and definitions, emphasizing the importance of data, learning algorithms, and learned models in the machine learning process.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.