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A Friendly Federated Learning Framework
FreeApache-2.0
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Federated learning is a distributed machine learning approach that enables the training of models without the need to share data. This project is a simple and easy-to-use federated learning framework that can be integrated with popular machine learning frameworks such as PyTorch, TensorFlow, JAX, and scikit-learn. It supports federated learning training, analysis, and evaluation, as well as the simulation of client-side operations. The framework includes a wealth of examples and is suitable for the development of privacy-preserving machine learning models in scenarios that require data protection, such as healthcare, government and corporate enterprises, and finance.

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