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How many nodes should exist within a hidden layer of a neural network?

How many nodes should exist within a hidden layer of a neural network?

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I understand that each node in an input layer corresponds to a variable and maybe even a node for bias; I do not understand the amount of nodes in a hidden layer. From all of the visualizations I have seen, there is always one more node in the hidden layer compared to the input layer. For example, in the image below there are two nodes that make up the input layer. Next, there are three nodes that make up the hidden layer. I understand combinatorics but I am totally missing something here. What dictates the amount of nodes in a hidden layer?

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