Interpolation of Functions

Related lectures (30)

Page 2 of 3

Covers revisions on calculus, derivation rules, interpolation, and tangent vectors.

Covers Lagrange interpolation using intervals to find accurate polynomial approximations.

Explores interpolation of regular functions, error analysis, convergence, and Chebyshev polynomials.

Explores neural networks, activation functions, backpropagation, and PyTorch implementation.

Explores real functions, covering parity, periodicity, and polynomial functions.

Explores barycentric coordinates, interpolation, and basis functions in the context of linear systems.

Explores the intuition behind transforms of the place and addresses audience questions on integral calculations and function choices.

Covers the least squares method for approximating data and handling errors.

Covers the basics of Newton interpolation and interpolation polynomials using Lagrange and Newton methods.

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