Federated Learning: Training Across Edge Devices Without Sharing Local Data
Introduction Federated learning is a machine learning approach designed for situations where data is distributed across many devices or organisations, and moving that data to a central server is risky, expensive, or not allowed. Instead of collecting raw data in one place, federated learning sends a model to where the data already lives—such as smartphones, […]