End-to-end MV grid fault risk scoring: feature engineering, tracked training, artefact versioning, API serving, monitoring-ready outputs
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Updated
Feb 19, 2026 - Python
End-to-end MV grid fault risk scoring: feature engineering, tracked training, artefact versioning, API serving, monitoring-ready outputs
A research framework for benchmarking risk-aware time-series models in aerospace PHM. It focuses on de-noising complex flight manifolds, evaluating model stability under multi-modal regimes, and ensuring prognostic generalisation through rigorous experimental auditing.
Real-time predictive maintenance system on STM32 with Zephyr RTOS. Multithreaded sensor data collection, circular buffering, and on-device anomaly detection for industrial equipment monitoring.
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