Summary

In this chapter, we introduced belief networks along with RBMs and explained how these can be developed into a DBN. We gave examples as to how both supervised and unsupervised DBNs can be implemented in TensorFlow, in order to make predictions on a dataset.

Moving on from this chapter, this book will dive into some more unsupervised learning approaches in the form of Monte Carlo methods and reinforcement learning.