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Mathematics of Big Data - Spreadsheets, Databases, Matrices, and Graphs (Hardcover) Loot Price: R1,981
Discovery Miles 19 810
You Save: R192 (9%)
Mathematics of Big Data - Spreadsheets, Databases, Matrices, and Graphs (Hardcover): Jeremy Kepner, Hayden Jananthan

Mathematics of Big Data - Spreadsheets, Databases, Matrices, and Graphs (Hardcover)

Jeremy Kepner, Hayden Jananthan; Foreword by Charles E. Leiserson

Series: MIT Lincoln Laboratory Series

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List price R2,173 Loot Price R1,981 Discovery Miles 19 810 | Repayment Terms: R186 pm x 12* You Save R192 (9%)

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The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies. Today, the volume, velocity, and variety of data are increasing rapidly across a range of fields, including Internet search, healthcare, finance, social media, wireless devices, and cybersecurity. Indeed, these data are growing at a rate beyond our capacity to analyze them. The tools-including spreadsheets, databases, matrices, and graphs-developed to address this challenge all reflect the need to store and operate on data as whole sets rather than as individual elements. This book presents the common mathematical foundations of these data sets that apply across many applications and technologies. Associative arrays unify and simplify data, allowing readers to look past the differences among the various tools and leverage their mathematical similarities in order to solve the hardest big data challenges. The book first introduces the concept of the associative array in practical terms, presents the associative array manipulation system D4M (Dynamic Distributed Dimensional Data Model), and describes the application of associative arrays to graph analysis and machine learning. It provides a mathematically rigorous definition of associative arrays and describes the properties of associative arrays that arise from this definition. Finally, the book shows how concepts of linearity can be extended to encompass associative arrays. Mathematics of Big Data can be used as a textbook or reference by engineers, scientists, mathematicians, computer scientists, and software engineers who analyze big data.

General

Imprint: MIT Press
Country of origin: United States
Series: MIT Lincoln Laboratory Series
Release date: July 2018
Authors: Jeremy Kepner • Hayden Jananthan
Foreword by: Charles E. Leiserson
Dimensions: 229 x 178 x 25mm (L x W x T)
Format: Hardcover
Pages: 448
ISBN-13: 978-0-262-03839-3
Categories: Books > Computing & IT > General theory of computing > Mathematical theory of computation
Books > Computing & IT > Applications of computing > Databases > General
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LSN: 0-262-03839-0
Barcode: 9780262038393

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