There are various types of architectures in neural networks. We can categorize DL architectures into four groups: Deep Neural Networks (DNNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Emergent Architectures (EAs).
Nowadays, based on these architectures, researchers come up with so many variants of these for domain-specific use cases and research problems. The following sections of this chapter will give a brief introduction to these architectures. More detailed analysis, with examples of applications, will be the subject of later chapters of this book.