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Computational and statistical methods for analysing big data with applications / Shen Liu, The School of Mathematical Sciences and the ARC Centre of Excellence for Mathematical & Statistical Frontiers, Queensland University of Technology, Australia, James McGree, The School of Mathematical Sciences and the ARC Centre of Excellence for Mathematical & Statistical Frontiers, Queensland University of Technology, Australia, Zongyuan Ge, Cyphy Robotics Lab, Queensland University of Technology, Australia, Yang Xie, The Graduate School of Biomedial Engineering, the University of New Spoutjh Wales, Australia.

Contributor(s): London : Academic Press is an imprint of Elsevier, c2016 copyright 2016Description: 194 pages ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780128037324
Subject(s): DDC classification:
  • 006.312 23
Summary: "Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data." --Publisher's description.
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Holdings
Item type Current library Call number Status Date due Barcode
Print Materials Main Library General Circulation 006.312 .L783 2016 (Browse shelf(Opens below)) Available 0119557

Includes bibliographical references and index.

"Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data." --Publisher's description.

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Text in English

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