SOON TO BE DEPRECATED - The TensorFlow bindings for PySyft
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Updated
May 30, 2020 - Python
SOON TO BE DEPRECATED - The TensorFlow bindings for PySyft
Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with privacy guarantees.
A simple federated learning implementation on MNIST dataset using PySyft. Main goal of the project was to get used to the PySyft federated learning functionality instead of using traditional PyTorch features.
Securing Collaborative Medical AI by Using Differential Privacy
The implementation of the "Robust Federated Learning by Mixture of Experts" study.
This repository will help you to understand how Federated learning can be implemented on Pima Indians Diabetic Dataset. It involves the use of OpenMined tool called Pysyft and Pytorch for implementation.
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