In many cases an activation function is notated as g (e.g. Andrew Ng's Course courses), especially if it doesn't refer to any specific activation function such as sigmoid.
However, where does this convention come from? And for what reason did g start to be used?
Topic activation-function notation deep-learning
Category Data Science
The addition of the activation layer creates a composition of two functions.
"A general function, to be defined for a particular context, is usually denoted by a single letter, most often the lower-case letters f, g, h."
So it comes down to the reason that he uses the hypothesis representation h(x)=wX+b which is a function, and that is wrapped by an activation function denoted as g. The choice of g seems to be purely alphabetical.
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