Lectures related to Determinants of Matrices: Properties and Applications

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

Explores the Eigen library for linear algebra, covering vectors, matrices, arrays, memory management, reshaping, and per-component operations.

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

Covers the properties and calculations of matrix determinants, including special cases and examples.