Lectures related to Numerical Methods: Iterative Techniques

Discusses numerical methods, focusing on stopping criteria, SciPy for optimization, and data visualization with Matplotlib.

Covers the Crank-Nicolson and Heun's methods, discussing uniqueness of solutions and truncation errors in numerical methods.

Covers the semester project on numerics, focusing on adaptive algorithms and multistep methods.

Covers the bisection method for finding zeros of continuous functions through iterative narrowing of intervals.

Covers the basics of numerical analysis and computational methods using Python, focusing on algorithms and practical applications in mathematics.

Explores the convergence of fixed point methods and the implications of different convergence rates.

Covers the Jacobi iterative method for solving electrostatic problems and discusses convergence and practical examples.