Lectures related to PCA: Principal Components Analysis

Examines conditions for the existence of invertible matrices satisfying specific matrix equations involving eigenvalues.

Explores subrepresentations of the regular representation in group theory, emphasizing properties and isomorphism between subrepresentations.

Explores Principal Component Analysis for dimensionality reduction and unsupervised feature selection.

Explores matrix rank and vector space inclusion through elementary row operations.

Explores bases, dimensions, and matrix ranks in vector spaces with practical examples and proofs.

Explores the row and column ranks of a matrix in linear algebra, emphasizing their calculation and relationship.