ML Application · Python

turbowatch

Hazem Ilahi@Dyaus2 · Atlas 62.8 · #20= builder

What it is

TurboWatch is an end-to-end predictive maintenance system for turbofan engines that combines gradient boosting and 1D-CNN remaining useful life models, health monitoring, cost-tuned alarms, SHAP explanations, and a retrieval-augmented generation copilot for querying maintenance manuals, with MLOps for drift detection and champion/challenger retraining.

Scored at1afc58f11 Nov 2026Changes since

Merit describes the code at this commit. Later pushes count once the owner rescans. How merit is scored

Where it counts

Machine Learning92%
MLOps78%
NLP & LLMs62%
Data Science55%
AI Agents18%

How much of the project is about each field, as scoring counts it. It ranks in the field it is most about.

What the judge found

Read from the project's code at its scored commit.

Strengths3

End-to-end integration of predictive maintenance modeling with retrieval-augmented generation for explainability.
Comprehensive MLOps practices including drift detection, champion/challenger retraining, experiment tracking via MLflow, and containerized deployment.
Strong documentation and reproducibility aids such as data/model cards, detailed README, and clear setup instructions.

Limitations

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Around it on the Machine Learning board

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