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[AI & ML]

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
go to website ↗github
personalized-federated-learning-for-privacy-preserving-and-scalable-iot-driven-smart-healthcare — preview
Personalized-Federated-Learning-for-Privacy--Preserving-and-Scalable-IoT-Driven-Smart-Healthcare repository preview
# README
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.
# tags
# install
npm install Personalized-Federated-Learning-for-Privacy--Preserving-and-Scalable-IoT-Driven-Smart-Healthcare
languages
Python100%
last commit3 months ago
licenseMIT
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