Lectures related to Linear Dependence of Vectors

Covers the Gram-Schmidt algorithm for orthonormal bases in vector spaces.

Covers exercises submission, a test announcement, and the Rank Theorem in linear algebra.

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

Covers determining vector spaces, calculating kernels and images, defining bases, and discussing subspaces and vector spaces.

Explores area determination, linear applications, matrix operations, and vector spaces.

Introduces linear algebra basics, including linear independence, injectivity, surjectivity, and bases in vector spaces.