Im currently learning neural networks and I see conflicting decsriptions of the dimensions of weight and input matrices on the internet. I just wanted to know if there is some convention which more people use than the other.
I currently define my input matrix X with the dimensions of:
(m x n)
Where m is the number of samples and n is the number of features.
And I define my weight matrices with the dimensions:
(a x b)
Where a is the number of neurons in the layer and b is the number of neurons in the last layer.
Is that conventional or should I change something?