ifri-mini-ml-lib 0.1.0

A lightweight machine learning library built from scratch by IFRI IA students

ifri_mini_ml_lib

ifri_mini_ml_lib is a reimplementation of the scikit-learn Python library from scratch.
This project is developed by IFRI AI students as part of the Concepts & Applications of Machine Learning course.

Features

• Implementation of core machine learning algorithms.
• Focus on understanding the inner workings of ML models.
• Lightweight and easy to use.
• Includes implementations for:
  • Classification (Decision Trees, KNN, Logistic Regression)
  • Regression (Linear, Polynomial, SVR)
  • Clustering (K-means, DBSCAN, Hierarchical)
  • Association Rules (Apriori, Eclat, FP-Growth)
  • Neural Networks (MLP)
  • Model Selection tools (Cross-validation, Grid Search, etc.)
  • Preprocessing utilities

Installation

You can install ifri_mini_ml_lib directly from PyPi:

pip install ifri-mini-ml-lib

Alternatively, you can install from source:

git clone https://github.com/your-username/ifri_mini_ml_lib.git
cd ifri_mini_ml_lib
pip install -e .

Documentation

For detailed documentation on the available modules and classes, please visit our documentation site.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License.

Acknowledgments

Thanks to the IFRI AI students and faculty who contributed to this project.