Training Pattern

With supervised training, the desired inputs and outputs are provided by the trainer. The network then classifies the inputs and compares the resultant outputs against the benchmark outputs. Any errors are back-propagated throughout the system, which forces the network to adjust the various parameter weights. This continuous tweaking process repeats over and over, giving the "deep learning" name to the network.