*3.8. Dense*

The dense layer is comprised by fully connected neurons both forward and backward. Every element of the input is connected with every neuron of this layer. In four out of five models, a dense layer can be seen at the end of the pipeline. The number of neurons in these layers is the number of classes in our dataset. For the third model, where TF-IDF tokenization takes place, we chose a simple DNN with 3 fully connected layer, which decreasing number of neurons for each subsequent layer. DNNs with multiple dense fully connected layers is shown to perform better than shallow DNNs [**?** ].
