Lecture

Unsupervised learning: Young-Eckart-Mirsky theorem and intro to PCA

In course

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Description

This lecture covers the Young-Eckart-Mirsky theorem, which is essential in unsupervised learning, and introduces Principal Component Analysis (PCA) as a method for dimensionality reduction and data visualization. The slides discuss the theorem, PCA concepts, and the application of PCA in various fields.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_rj3tjvfg

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Ontological neighbourhood

Information engineering

Machine learning: Unsupervised learning

Data science: Dimensionality reduction

Mathematics

Algebra: Linear algebra

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