Creating and fitting a deep neural network model

In this section, we will develop the model architecture, compile the model, and then fit the model.

Developing model architecture

The code used for developing the model is as follows:

# Initializing the model
 model <- keras_model_sequential()

# Model architecture
 model %>% 
 layer_dense(units = 8, activation = 'relu', input_shape = c(21)) %>% 
 layer_dense(units = 3, activation = 'softmax')

As shown in the preceding code, we start by creating a sequential model using the keras_model_sequential() function, which allows a linear stack of layers to be added. Next, we add layers to the model using the pipe operator, %>%. This pipe operator takes information...