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...
Nesta página do site você pode assistir ao vídeo on-line Federated Learning Demo Using the Flower Framework | Python, Tensorflow 2.0 duração hora minuto segundo em boa qualidade , que foi baixado pelo usuário Pratik Garai 22 Setembro 2021, compartilhe o link com seus amigos e conhecidos, no youtube este vídeo já foi visto 24,313 vezes e gostou 456 espectadores. Boa visualização!