Lectures related to Verification and validation

Explains Galerkin orthogonality in numerical methods and its stability criteria.

Explores numerical methods for the harmonic oscillator, focusing on stability and convergence in solving oscillatory systems.

Explores gradient and conjugate gradient methods for solving linear systems efficiently.

Covers high order ODEs, numerical methods, and stability criteria.

Introduces NumPy, focusing on array creation, manipulation, and its advantages for scientific computing.

Explores Legendre polynomials and their role in numerical integration techniques.

Covers faster gradient descent methods and projected gradient descent for constrained optimization in machine learning.