Federated Learning

Term definition

Federated learning is a machine learning technique that trains algorithms across multiple decentralized edge devices or servers holding local data samples, without exchanging their data. It matters for enterprise operations by enabling AI model training on sensitive or distributed data while preserving privacy and reducing data transfer costs.

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