Deep neural networks may have many layers in different patterns of connection within and between kayers and different learning rules. For example often a convolutional neural network may form the first stage of an image processing network. The choice of the number of layers, their types and sizes comprises the neural network architecture. Typically this is designed by a human, but sometimes some of the hyperparameters, such as the size of a pinch-point layer, may be tuned by a meta-level algorithm.
Used in Chap. 6: page 92; Chap. 8: page 113; Chap. 12: page 197; Chap. 14: page 231
Also known as architecture
Deep learning architecture – multiple layers, with varying connection topologies.
Convolutional neural network – often used as the first stage of an image processing neural netwrok
Different kinds of connection patterns between layers.