Scientific Methods: Numerical Analysis📊

A streamlined implementation of numerical methods for error estimation and polynomial interpolation,

Core Features

Error Analysis: Truncation, Round-off, and Propagation error studies.
Interpolation: Dual-method implementation (Newton & Lagrange) for function approximation.
Analysis: Study of Runge’s Phenomenon and polynomial sensitivity.

Here is a glimpse of the numerical convergence and interpolation accuracy achieved in this project:

Top: Error convergence analysis (Taylor Series) | Bottom: Interpolating polynomial vs. True function.

Python | NumPy | Pandas | Matplotlib

Name		Name	Last commit message	Last commit date
assets		assets
README.md		README.md
interpolation_and_errors.ipynb		interpolation_and_errors.ipynb
roots_comparison.ipynb		roots_comparison.ipynb