Federated Learning Support
Enables distributed training of machine learning models across multiple devices or nodes without sharing raw data.
Multi-Framework Compatibility
Supports federating workloads built with any machine learning framework.
Language Agnostic
Allows federated workloads to be implemented in any programming language.
Analytics and Evaluation
Includes tools for analyzing and evaluating federated learning processes and results.