Federated Learning

Definition

A machine learning technique that trains models across multiple decentralised devices or servers holding local data, without transferring the raw data to a central location. Federated learning addresses data privacy and sovereignty concerns by keeping sensitive data on-device while still enabling collaborative model improvement. It is particularly relevant in healthcare, finance, and telecommunications where data sharing restrictions are stringent.