Handbook of Big Data (Paperback)
  • Handbook of Big Data (Paperback)
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Handbook of Big Data (Paperback)

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£59.99
Paperback 480 Pages / Published: 11/09/2019
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Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical and computing ideas that can be readily applied in research and practice.

Offering balanced coverage of methodology, theory, and applications, this handbook:

Describes modern, scalable approaches for analyzing increasingly large datasetsDefines the underlying concepts of the available analytical tools and techniquesDetails intercommunity advances in computational statistics and machine learning

Handbook of Big Data also identifies areas in need of further development, encouraging greater communication and collaboration between researchers in big data sub-specialties such as genomics, computational biology, and finance.

Publisher: Taylor & Francis Ltd
ISBN: 9780367330736
Number of pages: 480
Weight: 885 g
Dimensions: 254 x 178 mm


MEDIA REVIEWS

"The book contains a nice mix of philosophical musings, survey articles and cutting-edge research. It was designed as 'a useful resource for seasoned practitioners and enthusiastic neophytes alike' . . . Enthusiastic neophytes are still left with plenty to get their teeth into. In summary, I am happy to recommend the book to those seeking to broaden their understanding of the underpinning methodologies for analysing Big Data." ~ Richard J. Samworth, University of Cambridge, UK

". . . Handbook of Big Data is the first compilation on this emerging subject in our field and is therefore highly recommended to all statisticians and computer scientists."
~The International Biometric Society

"The book strikes a great balance between the breadth and depth of recent research-active topics. It is an excellent reference book to keep for both academic researchers and industrial practitioners. It is also a good reference book for whoever teaches in the area of big data analysis.
~Journal of the American Statistical Association

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