Computational and statistical methods for analysing big data : with applications (Record no. 103055)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01808nam a2200181 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 978-0128037324 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 519.5 SHE |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Shen, Liu Et.al. |
| 245 ## - TITLE STATEMENT | |
| Title | Computational and statistical methods for analysing big data : with applications |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Boston |
| Name of publisher, distributor, etc. | Elsevier |
| Date of publication, distribution, etc. | 2016 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | viii, 194p. |
| Other physical details | 23cm; ; Hardbound |
| 500 ## - GENERAL NOTE | |
| General note | SRS Rs.7046.50/- |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. 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 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Big data |
| -- | Quantitative research |
| -- | Statistical methods |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Shen Liu; James McGree; Zongyuan Ge; Yang Xie |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="http://store.elsevier.com/product.jsp?isbn=9780128037324&pagename=search">http://store.elsevier.com/product.jsp?isbn=9780128037324&pagename=search</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Not for loan | Collection code | Home library | Current library | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GSB Collection | 02/12/2016 | 519.5 SHE | B2262 | 02/12/2016 | 02/12/2016 | Books |