R Deep Learning Essentials - Second Edition

Deep learning layers

In the earlier code snippets, we saw some layers for a deep learning model, including mx.symbol.FullyConnected, mx.symbol.Activation, and mx.symbol.Dropout. Layers are how models are constructed; they are computational transformations of data. For example, mx.symbol.FullyConnected is the first type of layer operation we matrix operation we introduced in Chapter 1, Getting Started with Deep Learning. It is fully connected because all input values are connected to all nodes in the layer. In other deep learning libraries, such as Keras, it is called a dense layer. 

The mx.symbol.Activation layer performs an activation function on the output of the previous layer. The mx.symbol.Dropout layer performs dropout on the output ...