Build a Federated Learning System on Android with Kotlin
Traditional machine learning often requires collecting training data on a central server. Federated learning takes a different approach: the model is sent to participating devices, training happens locally, and devices send model updates rather than their raw training data.
This tutorial explains how to design a federated learning prototype with Kotlin on Android.
Federated learning improves data locality, but it is not automatically private. Model updates can potentially leak information, so production systems need additional privacy and security mechanisms.
Architecture
