Federated learning is a distributed machine learning approach in which models are trained across many devices or institutions without centralizing raw data in one location. Each participant computes model updates locally and shares only gradients or weights, preserving the privacy of underlying data. Federated learning enables AI training on sensitive information such as medical records, financial transactions, and personal communications.
Federated Learning
Federated learning is a distributed machine learning approach in which models are trained across many devices or institutions without centralizing raw data in one location. Each participant computes model updates locally and shares only gradients or weights, preserving the privacy of underlying data. Federated learning enables AI training on sensitive information such as medical records, financial transactions, and personal communications.