A neural network constructs a model of a particular situation. Models are the basis of many human-like tasks. For example, in the task of navigating, we create a mental model of the route to take. Models are used frequently, and with the power and flexibility of neural network technology, it is possible to develop innovative modelling and predictive systems to find better solutions to a wide range of problems. Mathematical methods of model building have been available for many years.
Linear regression is a very widely known mathematical tool for modelling data.
The reason that this method derives its name however, is due to the fact that the mathematical relationship between the input data and the output produced by the model, is always linear. It is possible to introduce nonlinearities by means of modifying the inputs, for example, taking powers of the inputs. However, there are practical limits on the usefulness of models based on this type of approach. It is this capability which means that a neural network can capture any type of behaviour, no matter how complex. While there are still practical considerations that apply, neural networks represent a powerful approach to learning models based on observed data.