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Personalized-Federated-Learning-for-Privacy--Preserving-and-Scalable-IoT-Driven-Smart-Healthcare

A Personalized Federated Learning (PFL-HCare) framework for IoT healthcare. Features MAML meta-learning, Differential Privacy (RDP), and gradient quantization for efficiency. Includes a React/FastAPI dashboard for real-time monitoring.
Tisha-runwal
Tisha-runwal
Maintainer
268 stars
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Personalized-Federated-Learning-for-Privacy--Preserving-and-Scalable-IoT-Driven-Smart-Healthcare repository preview
About this project
A Personalized Federated Learning (PFL-HCare) framework for IoT healthcare. Features MAML meta-learning, Differential Privacy (RDP), and gradient quantization for efficiency. Includes a React/FastAPI dashboard for real-time monitoring. Maintained by Tisha-runwal on GitHub, where it has earned 268 stars from the community.
It's actively developed around differential-privacy, fastapi, federated-learning, and is a solid reference for anyone building with these tools.
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npm install Personalized-Federated-Learning-for-Privacy--Preserving-and-Scalable-IoT-Driven-Smart-Healthcare
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Python100%
Last updated3 months ago
LicenseMIT
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