This repository contains implementations of various numerical methods used in mathematics and computer science. These methods are essential for solving mathematical problems that might be impossible or too time-consuming to solve analytically. The implementations in this repository are done using Python and cover a range of techniques from root-finding algorithms to interpolation, regression, and integration.
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Root Finding:
- Newton-Raphson Method
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Interpolation:
- Newton Interpolation
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Regression and Curve Fitting:
- Linear Regression
- Polynomial Regression
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Linear Algebra:
- Gaussian Elimination
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Integration:
- Trapezoidal Rule
- Simpson's Rule
Make sure you have Python installed on your system. You will also need the following Python libraries:
- Numpy: Used for numerical computations. Install using:
pip install numpy
- Matplotlib: Used for data visualization. Install using:
pip install matplotlib
Each numerical method has its own directory with a dedicated Python file. To use a specific method, navigate to the respective directory and run the Python file associated with it.
For example, to run the Newton-Raphson method:
cd Integration
python integration.pyDetailed explanations and documentation for each numerical method can be found in the PDF files located in their respective directories.
Feel free to explore the implementations and learn about the underlying algorithms!
This project is licensed under the MIT License - see the LICENSE file for details.