Training neural networks

Training is the act of presenting the network with some sample data and modifying the weights to better approximate the desired function.

There are two main types of training: supervised learning and unsupervised learning.

Supervised learning

We supply the neural network with inputs and the desired outputs. Response of the network to the inputs is measured. The weights are modified to reduce the difference between the actual and desired outputs.

Unsupervised learning

We only supply inputs. The neural network adjusts its own weights, so that similar inputs cause similar outputs. The network identifies the patterns and differences in the inputs without any external assistance.