Lectures related to Eigenvalues and Minimal Polynomial

Covers the theory and examples of diagonalizing matrices, focusing on eigenvalues, eigenvectors, and linear independence.

Covers the concept of basis, linear transformations, matrices, inverses, determinants, and bijective transformations.

Explores eigenvalues, eigenvectors, and matrix diagonalization with examples and proofs.

Explains the diagonalization of matrices, criteria, and significance of distinct eigenvalues.

Explores algebraic and geometric multiplicities of eigenvalues in linear algebra.

Explores matrix representations of linear maps and their invariance, using examples and special cases.