Lectures related to Eigenvalues and Diagonalization

Diagonalization of Matrices and Least Squares

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

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

Diagonalization Cream: Distinct Eigenvalues

Covers the diagonalization of matrices with distinct eigenvalues and the importance of this process.

Explores diagonalization of matrices through eigenvalues and eigenvectors, emphasizing distinct eigenvalues and their role in the diagonalization process.

Diagonalization in 3D Linear Algebra

Explores diagonalization in 3D linear algebra, covering conditions for diagonalizability and eigenvectors.

Singular Value Decomposition: Applications and Interpretation

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.