Deep Learning Quick Reference

Summary

Stanford teaches an entire course only on reinforcement learning. It would have been possible to write an entire book just on reinforcement learning, and in fact that has been done many times. My hope for this chapter is to show you just enough to start you on your way towards solving reinforcement learning problems.

As I solved the Lunar Lander problem, it was easy to let my mind wander from toy problems to actual space exploration with deep Q network-powered agents. I hope this chapter does the same for you.

In the next chapter, I'll show you one last use of Deep Neural networks where we will look at networks that can generate new images, data points, and and even music, called Generative Adversarial Networks.