kanadsen / ME_773_PROJECT

FEDERATED LEARNING USING FLOWER ON NASA TURBOFAN DATASET

ME-773-PROJECT

Topic : Federated Learning for Predictive Maintainance

How to start federated Learning;

• Split the train and test set into two parts. One for central training c Study the following topics:

2. https://github.com/MALLI7622/Federated-Blockchain-Anamoly-Detection
3. https://github.com/ashishpatel26/Predictive_Maintenance_using_Machine-Learning_Microsoft_Casestudy
4. https://github.com/nevermined-io/fl-demo
5. https://blog.openmined.org/predictive-maintenance-of-turbofan-engines-using-federated-learning/
6. https://www.kaggle.com/datasets/behrad3d/nasa-cmaps
7. https://github.com/mohan696matlab/NASA-s-Turbo-Engine-Remaining-Useful-Life-prediction-using-machine-learning
8. https://dmg.org/pmml/v4-4-1/GeneralRegression.html
9. https://towardsdatascience.com/federated-learning-a-step-by-step-implementation-in-tensorflow-aac568283399
10. https://blog.paperspace.com/federated-learning-with-keras/
11. https://github.com/vaclavcadek/keras2pmml
12. https://support.pega.com/discussion/creating-pmml-python-r-and-pega
13. https://machinelearningmastery.com/extra-trees-ensemble-with-python/
14. https://www.wrighters.io/parameters-jupyter-notebooks-with-papermill/
15. https://stackabuse.com/reading-and-writing-lists-to-a-file-in-python/