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

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.

Integration of SplitNN for vertically partitioned data with OpenMined's PySyft

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

Material supporting the tutorial "Pursuing Privacy in Recommender Systems: The View of Users and Researchers from Regulations to Applications" held at the 15th ACM Conference on Recommender Systems in Amsterdam, Netherlands

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

An implementation of Federated Learning using Pytorch and PySyft

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.

Demonstration of application of Distributed Computing in Federated Learning for our Semester-8 Course on Distributed and Cloud Computing

Project entry for the Secure and Private AI Challenge, hosted by Udacity and sponsored by Facebook (May - August, 2019)

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

Securing Collaborative Medical AI by Using Differential Privacy

Repo for project : smog detection project at Udacity Project Showcase

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.

Repo including all the daily updates of #60daysofudacity Udacity Challenge

All Things Deep Learning Projects