Computational Learning in Engineering
Synopsis
Computational Learning in Engineering allows engineers to use computational learning techniques to develop solutions that promote or improve productivity in various domains. This book approaches several themes, ranging from conexionist approaches, learning techniques by data agglomeration, fuzzy logic and evolutionary computing methods, among others, always having in mind the use of techniques in a fast and efficient way, without neglecting, however, the accuracy that the subject deserves.
It is thus presented a set of the most used algorithms and a representative set of the real problems to which they can give solution. In order to make the book reasonably self-contained, each chapter includes a short introduction to the algorithm addressed, followed by simple ways of putting it into practice. In this sense, the mode of use of software that makes the algorithms available, their configuration and their use in real cases and data is presented.
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