Firstly, we want to thank you for giving this book a chance. With so many options available in the machine learning space for tutorials and training, you may be wondering why we chose to join the fray. Well, there are, in fact, a lot of resources out there for learning the basics of machine learning and deep learning (to shamelessly plug another Manning book, we recommend Andrew Trask’s Grokking Deep Learning to get up to speed there). But once people get a handle on the basics, where do they go from there?

We think a great next step for the newly-minted deep learning aficionado is to apply their new skills to the field of reinforcement learning. Reinforcement learning has seen tremendous success in the past few years and exciting results are happening every day, yet the landscape of truly beginner-level material in this area is comparatively sparse. Unlike deep learning, which has already infiltrated almost every major technology, reinforcement learning has just recently started to take form as a viable solution to practical problems. This means if you learn reinforcement learning now, you’ll be walking in on the ground floor of something that is surely going to surge in value in the near future.