Machine Learning and Metaheuristic Computation by Erik Cuevas (.ePUB)+

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File Size: 30.3 MB

Machine Learning and Metaheuristic Computation by Erik Cuevas, Jorge Galvez, Omar Avalos, Fernando Wario
Requirements: .ePUB, .PDF reader, 30.3 MB
Overview: Learn to bridge the gap between Machine Learning and metaheuristic methods to solve problems in optimization approaches. Few areas of technology have greater potential to revolutionize the globe than Artificial Intelligence. Two key areas of Artificial Intelligence, Machine Learning and metaheuristic computation, have an enormous range of individual and combined applications in Computer Science and technology. To date, these two complementary paradigms have not always been treated together, despite the potential of a combined approach which maximizes the utility and minimizes the drawbacks of both. Machine Learning and Metaheuristic Computation offers an introduction to both of these approaches and their joint applications. Both a reference text and a course, it is built around the popular Python programming language to maximize utility. It guides the reader gradually from an initial understanding of these crucial methods to an advanced understanding of cutting-edge Artificial Intelligence tools. For enthusiasts and practitioners in Machine Learning who may not be well-versed in metaheuristic computation, this book is an essential resource.
Genre: Non-Fiction > Tech & Devices

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