Mathematics of Big Data: Spreadsheets, Databases, Matrices, and Graphs (MIT Lincoln Laboratory Series)


Price: $65.65
(as of Oct 21,2019 16:58:52 UTC – Details)



Mathematics of Big Data presents a sophisticated view of matrices, graphs, databases, and spreadsheets, with many examples to help the discussion. The authors present the topic in three parts―applications and practice, mathematical foundations, and linear systems―with self-contained chapters to allow for easy reference and browsing. The algorithms are expressed in D4M, with execution possible in Matlab, Octave, and Julia. With exercises at the end of each section, the book can be used as a supplemental or primary text for a class on big data, algorithms, data structures, data analytics, linear algebra, or abstract algebra.

Jack Dongarra, Professor, University of Tennessee, Oak Ridge National Laboratory, and University of Manchester; coauthor of MPI: The Complete Reference, second edition, volume 1

In this era of big data, new methods for gaining insights promise to improve all aspects of our lives. This new textbook from Kepner and Jananthan is a fantastic resource for data scientists to understand the unifying mathematics for big data problems that covers everything from databases to graph analytics.

David A. Bader, Professor and Chair, School of Computational Science and Engineering, Georgia Institute of Technology



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