Java Deep Learning Cookbook

Constructing input layers for the network

Layer configuration is an important step in neural network configuration. We need to create input layers to receive the univariate time series data that was loaded from disk. In this recipe, we will construct an input layer for our use case. We will also add an LSTM layer as a hidden layer for the neural network. We can use either a computation graph or a regular multilayer network to build the network configuration. In most cases, a regular multilayer network is more than enough; however, we are using a computation graph for our use case. In this recipe, we will configure input layers for the network.