Federated Learning

Federated learning in cloud computing is a machine learning approach where models are trained across decentralized devices without sharing raw data. It enhances privacy by keeping data local while aggregating insights centrally. Federated learning is useful for applications requiring data privacy, such as personalized recommendations and healthcare analytics.