Linear and Nonlinear Regression in Python

The video tutorial covers interpolation techniques, including linear and cubic splines, using Scipy. It explains how to perform data approximation and error computation. The tutorial also discusses fitting thermo data with polynomial functions and analyzing errors. Finally, it demonstrates curve fitting for kinetic data using custom functions and parameter estimation.

What are the key differences between linear interpolation and cubic spline interpolation based on the text?

What steps are involved in plotting the original function and the interpolated values?

Discuss the importance of visualizing data when performing interpolation.

How can one evaluate the performance of the interpolation methods discussed?