I'm new to machine learning (so excuse my nomenclature), and not being a python developer, I decided to jump in at the deep (no pun intended) end writing my own framework in C++.
In my current design, I have given each neuron/cell the possibility to have a different activation function. Is this a plausible design for a neural network? A lot of the examples I see use the same activation function for all neurons in a given layer.
Is there a model which may require this, or should all neurons in a layer use the same activation function? Would I be correct in using different activation functions for different layers in the same model, or would all layers have the same activation function within a model?