Lectures related to Eigenvalue Geometric Multiplicity

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

Covers the properties and calculations of the determinant of a matrix.

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

Explores the properties and examples of diagonalizable matrices, emphasizing the relationship between eigenvectors and eigenvalues.

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

Covers the decomposition of a matrix into its eigenvalues and eigenvectors, the orthogonality of eigenvectors, and the normalization of vectors.