Lectures related to Non-Diagonalizable Case: Simple Eigenvalue (Theory)

Covers eigenvalues and eigenvectors, explaining their importance in linear algebra.

Covers the criteria for diagonalizing a matrix and provides illustrative examples.

Explains the step-by-step process of diagonalization for linear transformations on finite-dimensional vector spaces.

Covers diagonalization of matrices, eigenvectors, linear maps, and least squares method.

Covers eigenvalues, eigenvectors, and diagonalization of matrices.