Lecture

Statistical Learning: Fundamentals

Description

This lecture covers the basics of statistical learning, including different types of learning settings, supervised learning formalization, decision theoretic framework, risk minimization, and overfitting symptoms. It also delves into key concepts such as Tikhonov regularization, polynomial regression, dimensionality reduction, SVMs, neural networks, and ethical considerations in machine learning.

This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.

Watch on Mediaspace
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.