Data Science and Big Data Analytics: ACM-WIR 2018: 16 (Lecture Notes on Data Engineering and Communications Technologies, 16) - Image 1

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Springer Data Science and Big Data Analytics: ACM-WIR 2018: 16 (Lecture Notes on Data Engineering and Communications Technologies, 16)

Name: Data Science and Big Data Analytics: ACM-WIR 2018: 16 (Lecture Notes on Data Engineering and Communications Technologies, 16)
Brand: Springer
Price: 108.0 GBP
Availability: InStock

White

AI & Machine Learning

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Description

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence. From the Back Cover This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence. About the Author Dr. Durgesh Kumar Mishra  is a Professor (CSE) and Director of the Microsoft Innovation Centre at Sri Aurobindo Institute of Technology, Indore, India and visiting faculty at IIT-Indore. He has 24 years of teaching and 12 years of research experience. He has published more than 90 papers in refereed international/national journals and conferences including IEEE, ACM conferences and organized many conferences as General Chair and Editor. He is a Senior Member of the IEEE, CSI, ACM, Chairman IEEE MP Subsection, IEEE Computer Society Bombay Chapter. At present he is Chairman of CSI Division IV Communication at the National Level and ACM Chapter Rajasthan and MP State. Prof.  Xin-She Yang is an Associate Professor of Simulation Modelling at Middlesex University, London. Prof. Yang’s main interests are applied mathematics, algorithm development, computational intelligence, engineering optimisation, mathematical modelling, optimisation and swarm intelligence. His research projects have been supported by the National Measurement Office, BIS, Southwest Development Agency (UK), Euro Met, EPSRC, NPL, and the National Science Foundation of China. He is EEE CIS Task Force Chair of the BIKM, Technical Committee of Computational Finance and Economics of IEEE Computational Intelligence Society; Advisor to the International Journal of Bio-Inspired Computation; Editorial Board Member of Elsevier’s Journal of Computational Science; and Editor-in-Chief of the International Journal of Mathematical Modelling and Numerical Optimisation. Dr. Aynur Unal is a Strategic Adviser & Visiting Full Professor at the IIT Guwahati, India. She has created a product-focused engineering program using the cloud-based infrastructure. Her main interests include Ecologically and socially responsible engineering, Zero waste Initiative and Sustainable Green Engineering. Her research focuses on both rural and urban sustainable development, renewable energy, solar towers and pumps. She has taught at Stanford University, and worked in Silicon Valley to develop products for data mining from big data (Triada’s Athena I & II), Collaborative Design and Manufacturing, secure and private communication, and collaboration software platforms (Amteus, listed in LSE AIM)

Product Specifications

Brand: Springer
Colour: White
Format: paperback
ASIN: 9811076405
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 02 August 2018
Listed Since: 14 November 2017

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Springer Data Science and Big Data Analytics: ACM-WIR 2018: 16 (Lecture Notes on Data Engineering and Communications Technologies, 16)

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About as cheap as it gets — within 5% of the all-time low it hit 3 months ago.

Springer Data Science and Big Data Analytics: ACM-WIR 2018: 16 (Lecture Notes on Data Engineering and Communications Technologies, 16)

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