AI engineering glossary · AI ethics law product
What is federated learning?
Federated learning: A training approach in which many devices or organisations each train a model on their own local data and share only model updates with a central server, which combines them. Raw data never leaves its owner, which helps privacy, though updates can still leak information.
Federated learning: an example
Several hospitals jointly train a scan-analysis model, each keeping patient images on its own servers and sending only weight updates.
Related terms
- Differential privacy
- Secure multi-party computation
- Data minimization
- Membership inference attack
More AI ethics law product terms
- Four-fifths rule
- GDPR
- General-purpose AI model
- Global explanation
- High-risk AI system
- Historical bias
- Homomorphic encryption
- Human oversight
Where you learn it
Federated learning is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.