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Data Mining With Neural Networks: Solving Business Problems from Application Development to Decision Support

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In my position at IBM, I regularly brief executives, managers, and computer professionals on data mining and neural network technology. In my briefings, I cover the fundamentals of data mining and neural networks, and I also discuss specific applications relevant to the customers' businesses. Since time is usually limited, my goal is to quickly give them a basic understanding of data mining and to spark their imaginations so they can visualize how the technology can be used in their own enterprises. When I succeed, it is satisfying to see their excitement as they "ponder the possibilities." In the question-and-answer period following my presentations, I am invariably asked for a recommendation on a "good book on neural networks" so they can learn more. With few exceptions, these people do not want to know how neural networks work; they want to know how neural networks can be applied to solve business problems, using terminology they can understand and real-world examples to which they can relate.

While there are many neural network books available today, most focus on the inner workings of the technology. These texts approach neural networks from either a cognitive science or an engineering perspective, with a corresponding emphasis either on philosophical arguments or on a detailed treatment of the complex mathematics underlying the various neural network models. Other neural network books discuss academic applications, which have little or no relation to real business problems, and are full of C or C++ source code showing nitty-gritty implementation details. None of these titles would fit my definition of a "good book on neural networks" that is appropriate for a business-oriented audience.

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