Q:

ANNs traning, what happen in each epoche?

I have a question about the training of ANNs,
So I want to ask how the training is done for a set of input samples? Are there some relation between the size of the input set for training and the number of epoches for training, or it's totally independant?
For exemple, if my ANN has 4 inputs and for 2000 training's samples I get an input matrix of size 4x2000. So for each epoche of training, is that the whole matrix is loaded, or just one sample (training matrix column) is loaded for each epoche of traning?

A:

in each epoch of a NN all the weight values of the neurons are updated, all the nodes. Usually  the more neurons & layers & data you have the more epoches you need for a correct value for the weights, but there is not an equation for relationing epoches with neurons. 
For the training usually there is used Backpropagation algorithm (check wikpedia for a great example), that updates each weight once. The more epoches the more accurate your NN will be. Usually for the training you set 2 variables: max num of epoches and accuracy, and when one of the two is finally achieved you stop iterating.

