Hidden Layer in a Neural Network
The 256 hidden layer represent the 0 to 255 value given to each pixel to represent saturation of color for that pixel.
So I'm currently completing my Udacity Nanodegree and there is this one point that i'm not able to understand.
In the input layer we're taking 784 because the pixel of MNIST dataset is 28x28, but i don't understand why are they taking 256 hidden layer. Where did this 256 number came from?