Lectures related to Gram-Schmidt Algorithm: Orthogonalization and QR Factorization

Covers linear independence, bases, and coordinate systems with examples and theorems.

Explores vector subspaces in R4, symmetric matrices, basis vectors, and canonical forms.

Covers least squares solutions for linear systems using matrix operations and normal systems, illustrated with examples.

Explores the properties of invertible matrices, including unique solutions and linear independence.