Popular GitHub Repositories for Pysyft

Detect anomalies in network traffic data using Federated Machine Learning technique.

Study of data imbalance and asynchronous aggregation algorithm on Federated Learning system (using 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.

Credit Approval Classification Deep Learning Model using Differential Drivacy, Secure Multi-Party Computation, and Federated Learning

Healthcare-Researcher-Connector Package: Federated Learning tool for bridging the gap between Healthcare providers and researchers

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 project showcasing federated learning of model and testing on encrypted data and model

Multiple ML models classifying whether a person is depressed on not using time series data - 'Depresjon' and performing Federated Learning using OpenMined's PySyft library and SGD for optimisation.

All Things Deep Learning Projects

The implementation of the "Robust Federated Learning by Mixture of Experts" study.

Implementations notebooks and scripts of secured and private ai scholarship challenge from facebook.

The premise of this challenge is to build a habit of practicing new skills by making a public commitment of practicing the topics of Secure and Private AI program every day for 60 days.

:fire: Federated Learning Simplified with Frameworks

A collection of research and survey papers of differential privacy and federated learning

Exploring Federated Learning with TensorFlow, torch and Pysyft

Secure and Private AI Scholarship Challenge Udacity

The smartphones of the people probably carry the most valueable but also private data. Since using data promisses to be one of the best ways to fight back against COVID-19, it is highly desirable to get access. By using a Federated Learning approach with PySyft it is possible to learn from the private data right on the smartphone, with the data never leaving the device.

This project provides a Bluetooth application for secure remote activation of an autonomous vehicles, using PySyft for encrypted biometric authentication, PyTorch for anomaly detection, and Agentic AI for multilingual diagnostic reports.

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.