https://github.com/elcaiseri/machine-learning-from-scratch

Machine Learning using NumPy
https://github.com/elcaiseri/machine-learning-from-scratch

knn linear-regression logistic-regression machine-learning mlp naive-bayes numpy

Last synced: about 17 hours ago
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Machine Learning using NumPy

• Host: GitHub
• URL: https://github.com/elcaiseri/machine-learning-from-scratch
• Owner: elcaiseri
• Created: 2023-03-12T17:46:36.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-07-27T15:36:34.000Z (over 1 year ago)
• Last Synced: 2024-11-08T13:12:07.155Z (about 2 months ago)
• Topics: knn, linear-regression, logistic-regression, machine-learning, mlp, naive-bayes, numpy
• Language: Python
• Homepage:
• Size: 15.6 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

  





This repository contains a collection of classic machine learning algorithms implemented from scratch using only the Python NumPy library.

## Table of Contents

- [About](#about)

- [Algorithms](#algorithms)

- [To-Do](#to-do)

- [Usage](#usage)

- [Contributing](#contributing)

- [License](#license)

## About

Machine Learning from Scratch is a project aimed at deepening our understanding of fundamental machine learning algorithms. By implementing these algorithms using only the NumPy library, we gain insights into the underlying mathematical concepts and optimization techniques.

## Algorithms

Currently, the following algorithms have been implemented:

- k-Nearest Neighbors (knn.py)

- Linear Regression (linearRegression.py)

- Logistic Regression (logisticRegression.py)

- Naive Bayes (naiveBayes.py)

- Multi-Layer Perceptron (mlp.py)

Each algorithm is self-contained in its respective Python file.

## To-Do

- Add comments to explain the equations used in each algorithm.

- ~~Implement the Multi-Layer Perceptron (MLP) algorithm.~~

## Usage

You can use these implementations to explore and experiment with the behavior of classic machine learning algorithms. To get started, follow these steps:

1. Clone the repository: `git clone https://github.com/elcaiseri/Machine-Learning-from-Scratch.git`

2. Install the required dependencies: `pip install -r requirements.txt`

3. Open the Python files corresponding to the algorithm of interest.

4. Run the Python scripts to observe the algorithm's behavior.

## Contributing

We welcome contributions to improve existing implementations, add new algorithms, or fix issues. If you'd like to contribute, please follow the guidelines in [CONTRIBUTING.md](CONTRIBUTING.md).

## License

This project is licensed under the [MIT License](LICENSE).

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*If you find this project helpful or interesting, consider giving it a star! :star:*

*© 2023 [elcaiseri](https://github.com/elcaiseri)*

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