This repository contains Python codes of some of the most commonly used techniques in the field of computational mathematics. In the field of computational mathematics, the use of linear algebra is at its peak.

Some of the techniques implemented include finding the inverse of a matrix, reducing a matrix to its row-echlon form using Gauss, Gauss-Jacobi, and Gauss-Seidel. There are other techniques used commonly such as LU Decomposition, Sturm Sequences, whose implementations can be found here.

The repository also includes Python codes of finding the roots of polynomials. Finding the roots of a polynomial for polynomials of degree 2 is quite easy, but as the degree increasing, it is indeed a difficult task to find the roots. Therefore, in computational math, we use some techniques to find the approximate roots of the polynomial with some error tolerance.

Some of the methods implemented here are

• Bisection Method
• Iterative Method
• Secant Method
• Newton Raphson Method
• Regula Falsi Method

Disclaimer: The work included in this repository is still under development. The robustness of the codes and their efficacy can be improved by many folds