Let’s review this model and introduce some terminology.

Obviously, these raw feature variables form the input layer of the model.

All the computed neurons form the successive hidden layers.

The final output is computed from the last layer of neurons, which we call the output layer.

The result of all the weighted sums is referred to as the score.

The result transformed by the activation function is referred to as neurons.