Lectures related to Stochastic Optimization and Adaptive Gradient Methods

Explores matrix operations, linear systems, solutions, and the span of vectors in linear algebra.

Explores Singular Value Decomposition, low-rank approximation, fundamental subspaces, and matrix norms.

Introduces LU decomposition for efficient linear equation solving using matrix factorization.

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.