How does federated learning work?

Can you explain how federated learning works?

Sure! Federated learning is a machine learning approach that allows models to be trained across multiple decentralized devices while keeping the data localized.

What are the benefits of using federated learning?

The main benefits include enhanced privacy, reduced data transfer costs, and the ability to leverage data from multiple sources without compromising security.

How does it ensure data privacy?

Federated learning ensures data privacy by training models on local devices and only sharing model updates, not the actual data.

Can you give an example of where it's used?

Certainly! It's commonly used in mobile devices for predictive text and keyboard suggestions, where user data remains on the device.