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Overview

ReFedEz is a Python application and library designed to simplify the implementation and deployment of federated learning architectures. It provides:

• A command-line interface (CLI) for deploying servers and clients directly in their target environments, ensuring consistency and reproducibility.
• A Python library that seamlessly integrates into your machine learning code, enabling federated learning to work "like magic" with minimal modifications.

Why ReFedEz?

Federated learning is a powerful technique for training machine learning models across distributed data sources while maintaining privacy. However, popular tools like NVIDIA FLARE or Flower often include extensive features that demand significant time investment in reading documentation, configuring deployments, and testing ML models.

ReFedEz serves as the "fast.ai of federated learning" – a streamlined, beginner-friendly framework that prioritizes simplicity and rapid prototyping. It abstracts the underlying complexities, allowing researchers and developers to focus on their ML innovations rather than infrastructure challenges. Whether you're exploring federated learning concepts or scaling production systems, ReFedEz makes the process accessible and efficient.