End-to-end MLOps project for predictive maintenance using engine sensor data. Includes data versioning on Hugging Face, MLflow experiment tracking, CI/CD with GitHub Actions, and Dockerized Streamlit deployment for real-time engine failure classification.
python docker machine-learning scikit-learn classification sensor-data mlops mlflow github-actions huggingface streamlit end-to-end-ml redictive-maintenance
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Updated
Mar 8, 2026 - Jupyter Notebook