Shypd.aiThe largest open index of AI toolsTensorFlow Federated is an open-source framework for machine learning and other computations on decentralized data. It facilitates research and experimentation with Federated Learning, allowing models to be trained locally without centralizing sensitive data.
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TensorFlow Federated (TFF) is an open-source framework designed for machine learning and other computations on decentralized data. It specifically supports Federated Learning (FL), an approach where a shared global model is trained across many participating clients while their sensitive training data remains local. This framework enables developers to utilize included federated learning algorithms with their existing TensorFlow models and data, or to experiment with novel algorithms. TFF provides both a high-level Federated Learning (FL) API for applying federated training and evaluation, and a lower-level Federated Core (FC) API for expressing new federated algorithms. It includes a single-machine simulation runtime for experiments, making it suitable for researchers and developers exploring privacy-preserving machine learning.
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