An activation function is a function used in artificial neural networks which outputs a small value for small inputs, and a larger value if its inputs exceed a threshold.
If the inputs are large enough, the activation function "fires", otherwise it does nothing.
In other words, an activation function is like a gate that checks that an incoming value is greater than a critical number.
I compared Sigmoid and Softmax activation functions, then demonstrated the differences in Python.
You are welcome to provide your comments and subscribe to my RU-vid channel.
The Python code is uploaded into github.com/AIMLModeling/Softmax
5 фев 2023
