Intelligent Techniques for Data Science [Hardcover]

This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions./p>

The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for realworld applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.

Preface.- Introduction.- Data Analytics.- Basic Learning Algorithms.- Fuzzy Logic.- Artificial Neural Networks.- Genetic Algorithms and Evolutionary Computing.- Other Metaheuristics and Classification Approaches.- Analytics and Big Data.- Data Analytics Using R.- Appendix I: Tools for Data Science.- Appendix II: Tools for Computational Intelligence.

Rajendra Akerkar is a professor of information technology at Western Norway Research Institute, Norway. He has 23 years of research and teaching experience in artificial intelligent systems, semantic technologies and big data science. His recent research focuses on real world use of big data, and social media analysis in a wide set of semantic dimensions. He has held senior positions in the key academic conference committees, journal boards and review committees in those fields and he has supervised Ph.D. and research M.Sc. projects in intelligent systems, web intelligence and data science.  He has managed 12 international ICT initiatives, and data-intensive research & development projects for more than 17 years.

Dr Priti Srinivas Sajja (b.1970) joinlƒd