Up to now, numerous neural network architectures have been proposed and are in use. However, more or less all of them are based on a few core neural network architectures. We can categorize DL architectures into four groups:
- Deep neural networks
- Convolutional neural networks
- Recurrent neural networks
- Emergent architectures
However, DNNs, CNNs, and RNNs have many improved variants. Although most of the variants are proposed or developed for solving domain-specific research problems, the basic working principles still follow the original DNN, CNN, and RNN architectures. The following subsections will give you a brief introduction to these architectures.
