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9783662625200

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Mathematical foundations of big data analytics is a very welcome and timely addition to the growing area of big data analytics. ... Mathematical foundations are very carefully covered in each chapter, which justifies the title. There is a good listing of references for further study, as well as an index for easy reference. This book could be the basis for a one-semester graduate level course with an emphasis on mathematical foundations, supplemented by good programming projects. (S. Lakshmivarahan, Computing Reviews, July 5, 2021)

This book is apt for courses that introduce the fundamentals of data science/big data analytics at the graduate level. ... The book can be used in courses devoted to the foundational mathematics of data science and analytics. It should be noted that sound mathematical knowledge ... is required for reading. The case studies and exercises make it a quality teaching material. (Balint Molnar, Computing Reviews, August 19, 2022) Mathematical foundations of big data analytics is a very welcome and timely addition to the growing area of big data analytics. ... Mathematical foundations are very carefully covered in each chapter, which justifies the title. There is a good listing of references for further study, as well as an index for easy reference. This book could be the basis for a one-semester graduate level course with an emphasis on mathematical foundations, supplemented by good programming projects. (S. Lakshmivarahan, Computing Reviews, July 5, 2021)

Author Information

Vladimir Shikhman is a professor of Economathematics at Chemnitz University of Technology.David Müller is one of his doctoral students.

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