The hyperparameters that directly deal with the architecture of the deep learning model are called network architecture-specific hyperparameters. The different types of network-specific hyperparameters are as follows:
- Number of hidden layers
- Regularization
- Activation function as hyperparameters
In the following section, we will see how network architecture-specific hyperparameters work.