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Mathematics of Big Data | The MIT Press
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. Mathematics of Big Data by Kepner, Jananthan, Our eTextbook is browser-based and it is our goal to support the widest selection of devices available, from . The recent research evolution on big data has brought exciting aspiration to mathematicians, computer scientists and business professionals alike. However, the lack of a sound mathematical foundati Cited by: 2.
Mathematics of big data kepner pdf download
By Jeremy Kepner and Hayden Jananthan. 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, mathematics of big data kepner pdf download, 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 Modeland describes the application of mathematics of big data kepner pdf download arrays to graph analysis and machine learning, mathematics of big data kepner pdf download.
It provides a mathematically rigorous definition of associative arrays and describes the properties of associative mathematics of big data kepner pdf download 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.
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. 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.
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.
Jay R. Ramaswamy Sridharan and Antonio F. Search Search. Search Advanced Search close Close. Preview Preview. Leiserson The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies. Request Permissions Exam copy. Overview Author s Praise. Summary The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies.
Instructor Resources Downloadable instructor resources available for this title: solutions for instructors. Share Share Share email. Contributors Charles E. Endorsements Mathematics of Big Data presents a sophisticated view of matrices, graphs, databases, and spreadsheets, with many examples to help the discussion.
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Algorithms for Big Data (COMPSCI 229r), Lecture 1
, time: 1:26:05Mathematics of big data kepner pdf download
Mathematics of Big Data by Kepner, Jananthan, Our eTextbook is browser-based and it is our goal to support the widest selection of devices available, from . Mathematics of Big Data: Spreadsheets, Databases, Matrices, and Graphs Jeremy Kepner (MIT) and Hayden Jananthan (Vanderbilt) This book will be available from MIT Press in In the meantime, please see the related MIT Open Course Ware (OCW) class with many code examples: Signal Processing on Databases. The recent research evolution on big data has brought exciting aspiration to mathematicians, computer scientists and business professionals alike. However, the lack of a sound mathematical foundati Cited by: 2.
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