## Examples
The examples distributed here in this folder are regularly maintained by Scaleout and are part of the continuous integrations tests. 

### External examples
Below we maintain a list of examples provided both by the Scaleout core team and users. They may or may not be tested with the latest release of FEDn, please refer to the README of each specific project/example for detail. If you have a project that you want to include in this list, talk to a core developer in [Discord](https://discord.gg/CCRgjpMsVA).  

- [C++ version of the MNIST example](https://github.com/scaleoutsystems/examples) Also executes in Intel SGX TEE via Gramine.
- [Human activity recognition use case from the FEDn paper](https://github.com/scaleoutsystems/examples) IoT/cross-device. 
- [Sentiment analysis use case from the FEDn paper](https://github.com/scaleoutsystems/examples) NLP.
- [FedBird - Federated object detection for Baltic Seabirds](https://github.com/aidotse/fedbird) Project by AI Sweden and Zenseact. 
- [FEDn in AI Sweden EdgeLab](https://github.com/aidotse/EdgeLab/tree/main/tutorials/fedn) Instructions for running fully distributed FEDn in [EdgeLab](https://www.ai.se/en/data-factory/edge-lab).
- [FedLM - Federatad Electra.](https://github.com/Kungbib/fedLM) NLP project by the Swedish Royal Library. 
- [Fraud detection with a Keras auto-encoder (ANN encoder)](https://github.com/scaleoutsystems/FEDn-client-fraud_keras)  
- [VGG16 trained on cifar-10 with a PyTorch client (cross-silo)](https://github.com/scaleoutsystems/FEDn-client-cifar10-pytorch) 
- [Sentiment analysis with a PyTorch CNN trained on the IMDB dataset (cross-silo)](https://github.com/scaleoutsystems/FEDn-client-imdb-pytorch.git) 
