Intelligent Science And Intelligent Data Engineering


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Intelligent Science and Intelligent Data Engineering


Intelligent Science and Intelligent Data Engineering

Author: Yanning Zhang

language: en

Publisher: Springer

Release Date: 2012-07-23


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This book constitutes the proceedings of the Sino-foreign-interchange Workshop on Intelligence Science and Intelligent Data Engineering, IScIDE 2011, held in Xi'an, China, in October 2011. The 97 papers presented were carefully peer-reviewed and selected from 389 submissions. The IScIDE papers in this volume are organized in topical sections on machine learning and computational intelligence; pattern recognition; computer vision and image processing; graphics and computer visualization; knowledge discovering, data mining, web mining; multimedia processing and application.

Intelligent Science and Intelligent Data Engineering


Intelligent Science and Intelligent Data Engineering

Author: Jian Yang

language: en

Publisher: Springer

Release Date: 2013-02-11


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This book constitutes the proceedings of the third Sino-foreign-interchange Workshop on Intelligence Science and Intelligent Data Engineering, IScIDE 2012, held in Nanjing, China, in October 2012. The 105 papers presented were carefully peer-reviewed and selected from 429 submissions. Topics covered include pattern recognition; computer vision and image processing; machine learning and computational intelligence; knowledge discovery, data mining, and web mining; graphics and computer visualization; and multimedia processing and applications.

Intelligent Techniques for Data Science


Intelligent Techniques for Data Science

Author: Rajendra Akerkar

language: en

Publisher: Springer

Release Date: 2016-10-11


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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 real‐world 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.