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Use computational intelligence to drive more value from business analytics, overcome real-world uncertainties and complexities, and make better decisions. Drawing on his pioneering experience as an instructor and researcher, Dr. Les Sztandera thoroughly illuminates today's key computational intelligence tools, knowledge, and strategies for analysis, exploration, and knowledge generation. Sztandera demystifies artificial neural networks, genetic algorithms, and fuzzy systems, and guides you through using them to model, discover, and interpret new patterns that can't be found through statistical methods alone. Packed with relevant case studies and examples, this guide demonstrates:
Szandera shows how computational intelligence can inform the design and integration of services, architecture, brand identity, and product portfolio across the entire enterprise. He also shows how to complement computational intelligence with visualization, explorative interfaces and advanced reporting, thereby empowering business users and enterprise stakeholders to take full advantage of it. For analytics professionals, managers, and students.
LES SZTANDERA (Philadelphia, PA) is Professor of Computer Information Systems in the School of Business Administration at Philadelphia University's Kanbar College of Design, Engineering, and Commerce. He currently teaches in the iMBA program courses in Technical Competitive Intelligence and New Product Development, and is involved in several multidisciplinary industry sponsored research projects. His research interests include knowledge management and computational intelligence. His research has been funded by the US Departments of Defense and Commerce, NSF, State Supercomputer Centers, and the American Heart Association, among others. He received the highest, most prestigious appointment in the US Fulbright Scholars program in 2003, and was Fulbright Distinguished Chair at the School of Business and Economics (ISEG) in Lisbon, Portugal, where he taught in both MBA and Ph.D. programs.
1. Overview
2. Computational Intelligence Foundations
3. Computational Intelligence versus Statistical Approaches
4. Computational Intelligence at work
5. Future of Computational Intelligence
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