Welcome to the Mini Machine Learning Projects Repository—a curated collection of concise, practical, and impactful machine learning projects. Each project is designed to demonstrate core ML concepts, best practices, and real-world applications using modern Python libraries. This repository serves as a learning resource, portfolio showcase, and a foundation for further exploration in data science and machine learning.
| No. | Datasets | Tool |
|---|---|---|
| 01 | Employee Attrition Prediction | Python |
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## Included Projects
- **Employee Attrition Prediction:** Logistic Regression model to predict employee turnover.
Each project includes:
- Clean, well-documented Jupyter Notebook
- Dataset (or download instructions)
- Step-by-step data preprocessing, modeling, and evaluation
- Custom predictions/examples
- Project-specific README
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## Technologies Used
- Python 3.x
- Pandas, NumPy
- Scikit-learn
- Matplotlib, Seaborn
- Jupyter Notebook
- Google Collab
- VSC
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## Contribution Guidelines
Contributions are welcome! To add a new mini project:
1. Fork the repository
2. Create a new folder with your project name
3. Add your notebook, requirements.txt, and README.md
4. Submit a pull request with a clear description
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## License
This repository is licensed under the MIT License.
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## Author
- Devarsh S R
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## Contact & Support
For questions, suggestions, or collaboration opportunities, please open an issue or contact the author directly.
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Feel free to personalize the project list, author section, and contact details as needed!