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Deep Learning with TensorFlow - Second Edition by Md. Rezaul Karim, Giancarlo Zaccone

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Neural network architectures

The way that we connect the nodes and the number of layers present (that is, the levels of nodes between input and output, and the number of neurons per layer), defines the architecture of a neural network.

There are various types of architectures in neural networks. We can categorize DL architectures into four groups: Deep Neural Networks (DNNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Emergent Architectures (EAs). The following sections of this chapter will offer a brief introduction to these architectures. A more detailed analysis, with examples of applications, will be the subject of the following chapters of this book.

Deep Neural Networks (DNNs)

DNNs are ANNs which are strongly ...

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