DataGurukul

The Federated Learning approach eliminates the need to centralize the training data and allows ML models to be trained using data residing on mobile devices.

Several mobile devices can download the ML model to be used for the project. Only the model updates and not the entire training data is sent to the cloud.

At the central device or the data center, updates received in an encrypted form from all the users are aggregated for improving the shared model. The updated version of the model is then sent back to the participating devices from the centralized server.

Predicting the future isn't magic, It's Artificial Intelligence!