The terms shallow and deep refer to the number of layers in a neural network; shallow neural networks refer to a neural network that have a small number of layers, usually regarded as having a single hidden layer.
Shallow
Networks
•
The terms shallow and deep refer to the number of
layers in a neural network; shallow neural networks refer to a neural network
that have a small number of layers, usually regarded as having a single hidden
layer, and deep neural networks refer to neural networks that have multiple
hidden layers. Both types of networks perform certain tasks better than the
other and selecting the right network depth is important for creating a
successful model.
•
In a shallow neural network, the values of the
feature vector of the data to be classified (the input layer) are passed to a
hidden layer of nodes (neurons) each of which generates a response according to
some activation function, g, acting on the weighted sum of those values, z.
•
The responses of each unit in the hidden layer is
then passed to a final, output layer (which may consist of a single unit),
whose activation produces the classification prediction output.
Artificial Intelligence and Machine Learning: Unit V: Neural Networks : Tag: : Neural Networks - Artificial Intelligence and Machine Learning - Shallow Networks
Artificial Intelligence and Machine Learning
CS3491 4th Semester CSE/ECE Dept | 2021 Regulation | 4th Semester CSE/ECE Dept 2021 Regulation