Lectures related to Recommender Systems

Explores direct methods for solving linear equations and the impact of errors on solutions and matrix properties.

Covers linear systems, diagonal and triangular matrices, and LU factorization.

Covers the Singular Value Decomposition theorem and its application in decomposing matrices.

Covers the concept of Singular Value Decomposition (SVD) for compressing information in matrices and images.

Explores matrix inversion, conditions for invertibility, uniqueness of the inverse, and elementary matrices for inversion.