Context
I want to start using federated learning for my research on privacy-preserving healthcare analytics. The datasets involve patient records from three hospitals and we cannot share data across sites.
What I am looking for:
- Python frameworks that are actively maintained and used in research
- Any frameworks with good support for heterogeneous data distributions (non-IID)
- Something that has a reasonably gentle learning curve for a researcher (not a systems engineer)
I have looked at PySyft and Flower. Any experience with either, or other alternatives I should consider?