This event is hosted by SF Big Analytics Group. https://www.meetup.com/SF-Big-Analytics

Federated learning (FL) enables building robust and generalizable AI models by leveraging diverse datasets from multiple collaborators without moving data. We created NVIDIA FLARE as an open-source SDK to make it easier for data scientists to use FL in their research. The SDK allows existing machine learning and deep learning workflows adapted for distributed learning across enterprises and enables platform developers to build a secure, privacy-preserving offering for multiparty collaboration utilizing homomorphic encryption or differential privacy. The SDK is a lightweight, flexible, and scalable Python package and allows researchers to bring their data science workflows implemented in any training libraries (PyTorch, TensorFlow, or even NumPy), and apply them in real-world FL settings.

This talk will introduce the key design principles of NVIDIA FLARE and illustrate use cases (e.g., COVID analysis) with customizable FL workflows that implement different privacy-preserving algorithms.