Multiple deep learning frameworks have already implemented APIs for loading the F-MNIST dataset, including TensorFlow. For our implementation, we will be using Keras, another popular deep learning framework that is integrated with TensorFlow. The Keras datasets module provides a highly convenient interface for loading the datasets as numpy arrays.
Finally, we can start coding! For this exercise, we only need one Python module, which we will call cnn.py. Open up your favorite text editor or IDE, and let's get started.
Our first step is to declare the modules that we are going to use:
import loggingimport osimport syslogger = logging.getLogger(__name__)import tensorflow as tfimport numpy as npfrom keras.datasets import ...
