In this section, we'll show you how to build even more complex models with additional hidden layers. We'll adapt our single hidden layer model into a multilayer model known as a deep neural network. Then, we'll discuss choosing how many neurons and layers to use. Finally, we'll train the model itself, being patient, as this might take a while to compute.
Remember when we added a hidden layer of neurons to our logistic regression model? Well, we can do that again, adding another layer to our single hidden layer model. Once you have more than one layer of neurons, we call this a deep neural network. However, everything you learned before can be applied now. As in the previous sections of this chapter, you should make a fresh Python session and execute the code up to num_hidden1 in this section's code file. Then the fun starts.
