Predict the Remaining Useful Life (RUL) of aircraft engines using NASA's Turbofan Engine Degradation Simulation Data. Leverage machine learning for predictive maintenance to reduce costs and prevent failures.
A machine learning project for predictive maintenance of turbofan engines, featuring a Flask web application with visualizations, model predictions, and deployment via Docker. Includes datasets FD001-FD004 from the NASA Prognostics Data Repository.
Utilizing GDAL to georeference Images in a citizen science project
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