Neural networks are a hot topic in the business community today. Also marketed as intelligent techniques, business intelligence and data mining, many businesses are now realising the potential of neural networks to give them a competitive edge. Nevertheless most neural network books are written by electrical engineers for electrical engineers, with a high level of mathematics. Those few books aimed at the business community invariably focus exclusively on financial prediction. Consequently, Introduction to Neural Networks and Data Mining for Business Applications is a ground breaking text. With a minimum of mathematics, it shows the potential of neural networks to unlock hidden information in data of various industries including retail, marketing, insurance, telecommunications, banking and finance, and operations management. The book covers the development of neural network research and its impact on business; the early neural Perceptron model and its limitations; backpropagation, the most commonly used learning paradigm in business applications; self-organisation; and adaptive resonance theory. Data mining is then covered including the purpose, methodology, and concepts of directed and undirected knowledge discovery. Other intelligent techniques often used in conjunction with neural networks are also covered, including genetic algorithms, fuzzy logic, and expert systems. The text concludes with a discussion of the future of neural networks research and applications. Extensive business case studies are used throughout the text to demonstrate techniques.