Advanced Deep Learning with R

Autoencoder model

Now, we can specify the autoencoder network. The autoencoder's model and summary is as follows:

# Autoencoderae_model <- keras_model(inputs = input_layer, outputs = decoder)
summary(ae_model)______________________________________________________________________ Layer (type) Output Shape Param # ====================================================================== input_3 (InputLayer) (None, 28, 28, 1) 0 ______________________________________________________________________ conv2d_11 (Conv2D) (None, 28, 28, 32) 320 ______________________________________________________________________ max_pooling2d_5 (MaxPooling2D) (None, 14, 14, 32) 0 _______________________________________________________________________ conv2d_12 (Conv2D) ...