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Chen L.M., Su Z., Jiang B. Mathematical Problems in Data Science

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Chen L.M., Su Z., Jiang B. Mathematical Problems in Data Science
New York: Springer, 2016. - 213 p.
Explains the most current methods for solving cutting edge problems in data science and big data.
Provides problem solving techniques and case studies.
Covers a wide range of mathematical problems in data science in detail.
Topics:
Information Systems and Communication Service.
Computer Communication Networks.
Mathematics of Computing.
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Chen L.M., Su Z., Jiang B. Mathematical Problems in Data Science: Theoretical and Practical Methods

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Springer, 2016. — 219 p. — ISBN: 3319251252, 9783319251257 This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, different types of big data, geometric data structures, topological data processing, and various learning methods. For...
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