jessieli-avellar/ML-Industrial-Predictive-Maintenance

🛠️ End-to-End Predictive Maintenance Pipeline. Reducing industrial downtime with LightGBM, SMOTE & SHAP. Features: Boruta selection, Isotonic Calibration & XAI. Results: 0.986 ROC AUC | 85% Recall. Focused on ROI & production-ready deployment. Stack: Python, Scikit-Learn, XGBoost, Joblib.

22
/ 100
Experimental
No Package No Dependents
Maintenance 13 / 25
Adoption 0 / 25
Maturity 9 / 25
Community 0 / 25

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Jupyter Notebook

License

MIT

Last pushed

Apr 09, 2026

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