All Tools
F
Fine-tuningFreeOpen Source
FATE
Industrial federated learning framework for privacy-preserving AI
Apache-2.0
ABOUT
Organizations across finance, healthcare, and government hold valuable data they cannot share due to privacy regulations (GDPR, HIPAA, CCPA). FATE (Federated AI Technology Enabler) provides a production-grade federated learning platform with secure multi-party computation (MPC), differential privacy, and homomorphic encryption. It supports horizontal and vertical federated learning, enabling multiple parties to collaboratively train models where each party contributes different features or samples of the same dataset — without exposing raw data. FATE includes a complete cluster management dashboard and monitoring system for enterprise deployment.
INSTALL
pip install fateINTEGRATION GUIDE
1. Train a credit risk model across multiple banks without exposing individual customer data
2. Build a collaborative fraud detection system between financial institutions using vertical federated learning
3. Develop a healthcare outcome predictor across hospitals while complying with HIPAA data-sharing restrictions
4. Run secure multi-party computation for feature engineering across organizations without raw data leakage
5. Deploy a production federated learning cluster with the FATE management dashboard and operator monitoring
TAGS
federated-learningprivacydistributed-trainingpythonmachine-learningsecuritymulti-party-computation