We can access fashion-MNIST data from Keras using thedataset_fashion_mnist function. Take a look at the following code and its output:

# MNIST data
mnist <- dataset_fashion_mnist()
str(mnist)

OUTPUT
List of 2
 $ train:List of 2
  ..$ x: int [1:60000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ y: int [1:60000(1d)] 9 0 0 3 0 2 7 2 5 5 ...
 $ test :List of 2
  ..$ x: int [1:10000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ y: int [1:10000(1d)] 9 2 1 1 6 1 4 6 5 7 ...

Looking at the structure of the preceding data, we see that it contains train data with 60,000 images and test data with 10,000 images. All these images are 28 x 28 grayscale images. We know from the previous chapter that images can be represented as numeric data based on color and intensity. The independent variable x contains the intensity values, and the dependent variable y contains labels from 0 to 9.

The 10 different fashion items in the fashion-MNIST dataset are labelled from 0 to 9, as shown in the following table:

Looking at the preceding table, we may observe that developing a classification model for these images will be challenging as some categories will be difficult to differentiate.