Eigenvalues and EigenvectorsExplores eigenvalues, eigenvectors, and methods for solving linear systems with a focus on rounding errors and preconditioning matrices.
Diagonalization of MatricesExplores the diagonalization of matrices through eigenvalues and eigenvectors, emphasizing the importance of bases and subspaces.
PCA: Key ConceptsCovers the key concepts of Principal Component Analysis (PCA) and its practical applications in data dimensionality reduction and feature extraction.
Linear Algebra: Canonical BasisExplores the canonical basis in linear algebra, focusing on matrix representation, diagonalizability, and characteristic polynomials.
