February 2020
Intermediate to advanced
328 pages
8h 19m
English
Content preview from Deep Learning with R Cookbook
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Getting ready
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.
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