Layers in the convolutional neural networks

In this section, we will develop model architecture and then compile the model. We will also carry out calculations to compare the convolutional network with a fully connected network. Let's get started by specifying the model architecture.

Model architecture and related calculations

We start by creating a model using the keras_model_sequential function. The codes used for the model architecture are given as follows:

# Model architecture
model <- keras_model_sequential() 
model %>% 
         layer_conv_2d(filters = 32, 
                        kernel_size = c(3,3), 
                        activation = 'relu', 
                        input_shape = c(28,28,1)) %&gt...