What is federated learning?

What is federated learning?

Federated learning is a machine learning approach that allows models to be trained across multiple devices without sharing raw data.

How does it protect user privacy?

It keeps data on the device and only shares model updates, ensuring that sensitive information remains private.

What are some real-world applications of federated learning?

It's used in healthcare for predictive analytics, in mobile devices for personalized experiences, and in finance for fraud detection.

Are there any challenges with federated learning?

Yes, challenges include dealing with heterogeneous data, ensuring model convergence, and managing communication costs.