Building a Feedforward Neural Architecture
To build a neural network architecture using the KNIME Keras integration, you can use a chain of Keras layer nodes. The available nodes to construct layers are grouped by categories in the Keras->Layers folder in the Node Repository, such as Advanced Activations, Convolution, Core, Embedding, and Recurrent, to name just a few.
Each layer displayed in the Keras->Layers folder has a specialty. For example, layers in Advanced Activations create layers with units with specific activation functions; layers in Convolution create layers for convolutional neural networks; Core contains all classic layers, such as the Input layer to collect the input values and the Dense layer for a fully connected feedforward neural network; and so on.
We will explore many of these layers along the way in this book. However, in this current chapter, we will limit ourselves to the basic layers needed in a fully connected feedforward neural network.
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