In this recipe, we will use the MNIST data set that was used in the previous recipes, Implementing vanilla autoencoder and Dimensionality reduction using autoencoders. We will add random Gaussian noise to the normalized MNIST images and denoise them with a denoising autoencoder. We will refer to the normalized train and test datasets as x_train_norm and x_test_norm.