Unsupervised Learning: Principal Component Analysis

In course

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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.

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Instructor

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Official source

https://mediaspace.epfl.ch/media/0_8v0o3wae

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Ontological neighbourhood

Mathematics

Algebra: Linear algebra

Biology

Genetics: Genomics

Information engineering

Data science: Dimensionality reduction

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