ML-Algorithms-Hub

A comprehensive collection of Machine Learning algorithms, showcasing implementations in Python for supervised, unsupervised, and reinforcement learning techniques. This repository is designed for anyone looking to learn, experiment, or reference core machine learning concepts.

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Features

• Supervised Learning
  • Regression Algorithms (e.g., Linear Regression, Neural Networks, Random Forests)
  • Classification Algorithms (e.g., Logistic Regression, SVM, KNN)
• Unsupervised Learning (coming soon!)
  • Clustering (e.g., K-Means, DBSCAN)
  • Dimensionality Reduction (e.g., PCA)
• Reinforcement Learning (planned!)
  • Value-Based Methods (e.g., Q-Learning)
  • Policy-Based Methods (e.g., DDPG)

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Getting Started

1. Clone the repository:

   git clone https://github.com/YourUsername/ML-Algorithms-Hub.git
   cd ML-Algorithms-Hub

2. Install dependencies:

   pip install -r requirements.txt

3. Run examples:
   • Navigate to a folder (e.g., supervised/regression/) and execute:

     python linear_regression.py

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Contribution

Contributions are welcome! Feel free to open a pull request or submit an issue.

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License

This project is licensed under the MIT License - see the LICENSE file for details.

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