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1. Understanding Federated Learning 1.1 Definition and Core Concepts Federated Learning (FL) is a distributed machine learning approach where model training takes place across multiple local nodes (clients), which never share raw data. Instead, individual devices train a shared global model on their own data and send only updates—such as gradien