A collection of reusable scripts and utilities designed to optimize and accelerate Machine Learning workflows.
The goal of this repository is to modularize repetitive tasks such as data cleaning, metric visualization, preprocessing, and model evaluation, allowing Data Scientists and Machine Learning practitioners to focus on modeling rather than writing boilerplate code.
The repository is organized by standalone Python scripts:
- Automated data preprocessing pipeline: it handles common feature engineering tasks through a configurable pipelin. It detects features, applies appropriate transformations, generates engineered features based on common strategies, handles missing data
- Model fine-tuning manager:
🤝 Contributing
Contributions are welcome! If you have a useful script you'd like to share:
- Fork the repository.
- Create a new branch (git checkout -b feature/new-utility).
- Make your changes and commit (git commit -m 'Add new normalization function').
- Push to the branch (git push origin feature/new-utility).
- Open a Pull Request.
This repository was inspired by the article 5 Essential Python Scripts for Intermediate Machine Learning Practitioners on Machine Learning Mastery.
Special thanks to the author, Bala Priya C, for the insights that laid the foundation for this work.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
Made with ❤️ by srgee - If you found this useful, please give the repo a ⭐!