In this chapter, we outlined some new directions for deep learning research. We introduced core concepts behind popular deep learning-based generative modeling techniques, such as the Generative Adversarial Network.
We also discussed the key ideas behind capsule networks and what problems they aim to solve. Finally, we covered a number of novel application domains where deep learning is being applied today. We described these applications in detail and also showed how deep learning models are being used to achieve superior performance in these domains.
In this book, we have attempted to bring together key ideas in deep learning from a practitioner's perspective. We sincerely hope you like this book and provide us with feedback to improve future editions.
