This project is a collection of Numerical Methods algorithms implemented in Python during my university studies. This repository serves as a knowledge archive and demonstrates my programming and computational mathematics skills.
- Language: Python 3
- Libraries: The project relies mainly on standard libraries and some mathematical packages, showcasing native implementations of formulas and algorithms.
The tasks are divided into individual laboratory sessions, covering various numerical problems:
- Lab1 - Lab3: Interpolation (e.g., Newton's interpolation polynomials, generalized Horner's scheme).
- Lab5 - Lab9: Advanced numerical methods for solving systems of equations, numerical integration, and finding roots (implementations depend on the specific lab session).
Note: The lab numbers correspond to the original course structure.
- Calculating the coefficients of a Newton polynomial using the divided differences method.
- Evaluating a polynomial using Horner's scheme.
- (and other optimization and numerical algorithms discussed during the course)
This project demonstrates:
- The ability to translate complex mathematical formulas into functional code.
- Working with optimization algorithms and data structures.
- Writing clean and efficient Python code.