Lecture

Unsupervised Learning: Principal Component Analysis

Description

This lecture covers unsupervised learning, focusing on Principal Component Analysis (PCA) with motivating examples such as mapping human genome and people in Europe. It also discusses the Singular Value Decomposition (SVD) and the Young-Eckart theorem.

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.