Lectures related to Lanczos algorithm

Covers the process of solving a linear system in numerical flow simulation using direct methods like Gaussian elimination and the TDMA algorithm.

Explores the optimality of convergence rates in convex optimization, focusing on accelerated gradient descent and adaptive methods.

Explores manipulation of 3D arrays, barycenters, shape matrices, Jacobians, eigendecomposition, and visualization in elastic solids.

Covers the Newton-Raphson method, Jacobian matrix, and iterative schemes for solving nonlinear equations.

Explores the application of matrices and eigendecompositions in networks.

Explores data manipulation, exploration, and visualization in data science projects using Python.