Build, simulate, and deploy federated learning at scale with the core Flower Framework. Easily federate existing machine learning projects with the Flower Python SDK.

Partition datasets for federated learning using framework agnostic, reproducible, and thoroughly tested flwr-datasets library.

Easily reproduce and build upon well-known research results with Flower Baselines.

Build and deploy federated learning clients at scale with Flower. Easily federate Android on-device training with the Flower Android SDK.

Build and deploy federated learning clients at scale with Flower. Easily federate iOS on-device training with the Flower iOS SDK.

Federate native on-device training with the Flower C++ SDK (preview). Code example available, full docs coming soon.

Start easily by building on top of full Flower example projects covering a wide range of ML frameworks, platforms, and scenarios.

A lot more projects are coming soon so be sure to stay tuned! Connect with us on our Slack!