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WIP: Fine Grained Workflow API Tutorial
This PR:
- Represents a first in a tutorial series on demystifying federated learning - which will walk through the considerations when implementing an FL framework at a low level
- Demonstrates through the OpenFL Workflow API the importance of:
- Security for FL
- Reducing Communication cost
- Introduces methods for manipulating model weights and applying compression
- Demonstrates ease of implementing exfiltration attacks through models
- Performs a comparison between compression and it's effect on final model accuracy
The tutorial can be launched through Google Colab here:
Todo:
- [ ] Refactor low level interfaces from notebook into
openfl.experimentalnamespace (i.e.openfl.experimental.model,openfl.experimental.compression)