What is the OpenFL Tool Assembly?
OpenFL is an open-source Python library for federated learning, originally developed by Intel Labs and now a Linux Foundation project. OpenFL enables organizations to collaboratively train and evaluate machine learning models without sharing sensitive data. It is framework-agnostic, supporting TensorFlow, PyTorch, and other ML libraries, and is designed for scalability, security, and ease of integration with privacy-preserving technologies.
What can you use the OpenFL Tool Assembly for?
- Large-scale federated learning across organizations
- Secure, privacy-preserving analytics and model training
- Integration with trusted execution environments (TEEs)
- Healthcare, finance, and cross-institutional collaborations
Limitations/Remarks
- Setup and familiarity with security features required for optimal use
- Complexity in deployment for large federations
Specific Use Cases/Applications
- Healthcare data analysis across multiple hospitals
- Financial modeling with privacy constraints
- Federated learning in regulated industries
How to access the OpenFL Tool Assembly?
- Official Documentation
- GitHub Repository
- Install via pip:
pip install openfl
References
- OpenFL Documentation
- OpenFL GitHub
- Sheller, M.J. et al. (2020). Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data. Nature. Link
Original Framework Contributors
- Intel Labs
- OpenFL Community
For a full list, see the OpenFL GitHub contributors.
More information
Training
Affiliations Contributors
Editor
KU Leuven / University of UHasselt