Federated Learning Demo Using the Flower Framework | Python, Tensorflow 2.0
In this video, I take you through a brief explanation of how Federated Learning works and introduce you to one of the python frameworks used to implement the same. I use Tensorflow 2.0 to create the models and MNIST as the dataset.
Flower is a python framework used to implement Federated Learning. With just a few lines of code, convert your ordinary ML/DL code to a Federate architecture. Best part, no need to learn any new deep learning framework (if you already know one, that is) for support with flower as it supports all other deep learning frameworks (as long as the weights of the models can be extracted as a Numpy Array).
Flower documentation : https://flower.dev/
Code used in this demo : https://github.com/PratikGarai/MNIST-...
The presentation : https://docs.google.com/presentation/...
Image credits : https://ai.googleblog.com/2017/04/fed...
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