Yemdjih Kaze Nasser created FINCN-353:
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Summary: Research and implement a federated learning model
Key: FINCN-353
URL: https://issues.apache.org/jira/browse/FINCN-353
Project: Fineract Cloud Native
Issue Type: Sub-task
Reporter: Yemdjih Kaze Nasser
With the deficiency of consistent data and available datasets, it's really
challenging to build a good model for our credit scorecard. This gives the
advantage to use federated learning to train our models based on data in client
devices without copying the data to a central unit hence preserving the client
anonymously while building a robust model.
The aim here will be to research and implement a federated learning
algorithm/model. For starters, this can be done with a simulation environment
locally.
FYI: I think it will be easier to implement this using [TensorFlow
Federated|[https://www.tensorflow.org/federated].] Here is guide that can help
to get started: [Federated Learning for Image Classification | TensorFlow
Federated|https://www.tensorflow.org/federated/tutorials/federated_learning_for_image_classification]
TensorFlow is distributed under the Apache 2.0 Licence so we shouldn't face any
problem with Licencing conflicts.
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