[jira] [Created] (FINCN-353) Research and implement a federated learning model

["Yemdjih Kaze Nasser (Jira)" <ji...@apache.org>]

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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