How do we train a neural network? Basically, we will provide the with a set of input data as well as the results we expect to see, which correspond to those inputs. That data is then run through the network until the network understands what we are looking for. We will train, test, train, test, train, test, on and on until our network understands our data (or doesn't, but that's a whole other conversation). We continue to do this until some designated stop condition is satisfied, such as an error rate threshold. Let's quickly cover some of the terminology we will use while training neural networks.
Back propagation: After our data is run through the network, we to validate that data what we expect to be the correct output. We do this by propagating backward (hence backprop or back propagation) through each of the Hidden Layers of our network...
