Regardless of the specifics involved, applying a neural network is a substantial departure from traditional approaches. Neural networks do not require the explicit coding of the problem. For example, to generate a model that performs a sales forecast, a neural network only needs to be given raw data related to the problem. The neural network sorts through this information and produces an understanding of the factors impacting sales. The model can then be called upon to provide a prediction of future sales given a forecast of the key factors.
Neural networks constitute a powerful tool for data mining.
Data mining has become quite popular recently and really involves the extraction of knowledge from information. Organizations have more and more data from which they need to extract key trends in order to run their businesses more efficiently and improve decision making. Applications of neural networks are numerous. Many receive their first introduction by reading about the applications of the techniques in financial market predictions. Claims are made by several well-known investment groups that at least some of their technical analysis of financial markets and portfolio selection is performed with neural networks.