Numerical Methods in Python

This repository contains Python implementations of fundamental numerical methods used in scientific and engineering computations.
The project is divided into three main modules covering equation solving, systems of equations, and interpolation techniques.

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📌 Features

1️⃣ Solving Non-Linear Equations

Implemented methods:

• Bisection Method
• False Position Method
• Newton–Raphson Method
• Secant Method
• Fixed-Point Iteration Method

These methods are used to find roots of single-variable non-linear equations.

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2️⃣ Solving Systems of Linear Equations

Implemented methods:

• Jacobi Iteration Method
• Gauss–Seidel Method
• Relaxation Method

These iterative techniques are useful for solving large systems of linear equations efficiently.

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3️⃣ Interpolation & Curve Fitting

Implemented methods:

• Newton’s Divided Forward Interpolation
• Lagrange Interpolation
• Curve Fitting using Least Squares Method

These methods estimate unknown values and fit curves based on given data points.

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🧠 Technologies Used

• Language: Python 3
• Libraries:
  • sympy
  • numpy
  • scipy

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📦 Installation

Make sure Python 3 is installed, then install the required libraries using:

  pip install sympy numpy scipy

Make Executable File

  pip install pyinstaller
  pyinstaller --onefile your_script.py