Provides a review of linear algebra concepts crucial for convex optimization, covering topics such as vector norms, eigenvalues, and positive semidefinite matrices.
Covers solving linear equations, focusing on systems with zero, one, or infinite solutions, and introduces matrices as a powerful tool for efficient solution.