The Fashion MNIST Dataset contains 70,000 images which include 60,000 training images and 10,000 testing images. Each example is a 28x28 grayscale image which is associated with 10 different classes. This dataset is divided into 6 training batches and 1 test batch. The batch size is 10,000.
Execution Process
For the execution of image classification of Fashion MNIST data using Federated Learning, we have used two approaches first manually dividing the data and modelling and other using Pysyft hooked with Pytorch.
