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FEDn is a production-ready federated learning platform that enables organizations to collaboratively train machine learning models across distributed cloud and edge environments while keeping sensitive data secure and local, with out-of-the-box support for major ML frameworks. It integrates with existing ML workflows, offers flexible deployment options, and provides enterprise-grade security features such as encryption and token authentication to protect data and model contributions. The platform provides an SDK, tutorials, and open-source client APIs in Python, C++, and Kotlin, with examples and guides on GitHub for working with frameworks like TensorFlow, PyTorch, scikit-learn, and Hugging Face.
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