Lectures related to PCA and BBP Phase Transition

Explores eigenvalue problems, iterative methods, convergence properties, and applications in computational physics.

Explores diagonalization of matrices, conditions, invertibility, rank, nullity, and eigenvectors.

Discusses quadratic forms, matrix diagonalization, and their applications in optimization problems.

Introduces Matlab basics, error handling, and billiards project concepts.

Covers diagonalizing matrix A into VDV-1, stability of Euler method, and solving systems with progressive and retrograde Euler diagrams.

Explores efficient determinant calculations using triangular matrices and specific row/column selections for simplification.

Covers Principal Component Analysis for dimension reduction in biological data, focusing on visualization and pattern identification.

Covers the decomposition of matrices into triangular blocks and spectral decomposition.