Working with the CIFAR10 dataset

For illustrating the use of pretrained models with new data, we will make use of the CIFAR10 dataset. CIFAR stands for Canadian Institute For Advanced Research, and 10 refers to the 10 categories of images that are contained in the data. The CIFAR10 dataset is part of the Keras library and the code for obtaining it is as follows:

# CIFAR10 data
data <- dataset_cifar10()
str(data)
OUTPUT
List of 2
 $ train:List of 2
  ..$ x: int [1:50000, 1:32, 1:32, 1:3] 59 154 255 28 170 159 164 28 134 125 ...
  ..$ y: int [1:50000, 1] 6 9 9 4 1 1 2 7 8 3 ...
 $ test :List of 2
  ..$ x: int [1:10000, 1:32, 1:32, 1:3] 158 235 158 155 65 179 160 83 23 217 ...
  ..$ y: num [1:10000, 1] 3 8 8 0 6 6 1 6 3 1 ...

In the preceding code, we can observe the following:

• We can read the dataset using the dataset_cifar10() function.
• The structure of the data shows that there are...