This repository contains three Jupyter notebooks for numerical analysis tasks as part of homework assignments.
Covers solving a system of linear equations using the Gauss-Seidel method, deriving Lagrange polynomials, and performing quadratic curve fitting. Includes both manual calculations and Python implementations.
Focuses on finding roots of a transcendental equation using bisection, Newton-Raphson, and secant methods. Provides performance comparisons of each method with varying tolerances and iterations.
Includes numerical differentiation using the four-point method, integration using Trapezoidal and Simpson's rules, and solving an initial value problem with the Runge-Kutta method.