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Federated learning is a machine learning approach that trains models without moving raw data. Instead of centralizing sensitive datasets, each participant — whether a smartphone, enterprise, or hospital — trains a shared model locally and sends encrypted updates to a central server. The result is a continuously improving global model, built ...
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