Keras is a high-level neural networks API, written in Python and capable of running on top of Tensorflow, CNTK or Theano. It was developed with a focus on enabling fast experimentation. In this blog, we are going to cover one small case study for fashion mnist.
Fashion-MNIST is a dataset of Zalando’s article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28×28 grayscale image, associated with a label from 10 classes. Zalando intends Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.
The end result wasn’t that great, but Shubham was using a sequential model rather than a convolutional neural network, so you can probably take this as a starting point and improve upon it.