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ML examples: - credit_scoring: Credit risk prediction with HMEQ data - disease_prediction: Healthcare ML on encrypted records - cifar: Encrypted image classification - federated_learning: Distributed FHE training - hybrid_model: Mixed FHE/plaintext inference Deployment: - breast_cancer: Cancer detection API - sentiment_analysis: Encrypted NLP - server: FHE inference server Blockchain: - hardhat-template: Solidity + FHE - react-template: Full dApp with FHE
Lux FHE Examples
Real, working examples for Fully Homomorphic Encryption development.
ML Examples (ml/)
Production-ready machine learning on encrypted data:
| Example | Description | Data |
|---|---|---|
| credit_scoring/ | Credit risk prediction | HMEQ dataset |
| disease_prediction/ | Healthcare predictions | Medical records |
| cifar/ | Image classification | CIFAR-10 |
| federated_learning/ | Distributed training | - |
| hybrid_model/ | Mixed FHE/plaintext | - |
Quick Start
cd ml/credit_scoring
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
jupyter lab CreditScoring.ipynb
Deployment Examples (deployment/)
Production deployment patterns:
| Example | Description |
|---|---|
| breast_cancer/ | Cancer detection API |
| sentiment_analysis/ | NLP on encrypted text |
| server/ | FHE inference server |
Blockchain Examples (blockchain/)
FHE for smart contracts:
| Example | Description |
|---|---|
| hardhat-template/ | Solidity + FHE |
| react-template/ | React dApp + FHE |
Requirements
- Python 3.10+
- For ML:
pip install torus-ml - For blockchain: Node.js 18+
Related
- luxfhe/docs - Documentation
- luxfhe/handbook - Deep dive
- luxfhe/workshop - Tutorials
License
Apache 2.0