Lectures related to Piecewise Linear Interpolation and Spline Interpolation

Explores cubic splines and least-squares approximation, focusing on interpolation methods and error analysis.

Covers the Lagrange polynomial interpolation method and error analysis in function approximation.

Covers distributions, interpolation spaces, convergence, and the concept of dual spaces.

Covers the optimization of error in polynomial interpolation, focusing on minimizing the error by strategically placing interpolation points.

Explains Newton's method of order 2 for finding function zeros.

Covers advanced numerical analysis topics including deep neural networks and optimization methods.

Explores B-spline properties, gradient operators, interpolation, and differentiation filters in image processing.

Explores numerical differentiation and integration methods, emphasizing the accuracy of finite differences in computing derivatives and integrals.