Machine Learning Quick Reference

Hyperparameters

Hyperparameters are one of the building blocks of the deep learning network. It is an element that determines the optimal architecture of the network (for example, number of layers) and also a factor that is responsible for ensuring how the network will be trained.

The following are the various hyperparameters of the deep learning network:

• Learning rate: This is responsible for determining the pace at which the network is trained. A slow learning rate ensures a smooth convergence, whereas a fast learning rate may not have smooth convergence.
• Epoch: The number of epochs is the number of times the whole training data is consumed by the network while training. 
• Number of hidden layers: This determines the structure of the model, ...