Network Models for Data Science: Theory, Algorithms, and Applications - Tapa dura

Izenman, Alan Julian

 
9781108835763: Network Models for Data Science: Theory, Algorithms, and Applications
Tapa dura
ISBN 10: 1108835767 ISBN 13: 9781108835763
Editorial: Cambridge University Press, 2023

Sinopsis

This text on the theory and applications of network science is aimed at beginning graduate students in statistics, data science, computer science, machine learning, and mathematics, as well as advanced students in business, computational biology, physics, social science, and engineering working with large, complex relational data sets. It provides an exciting array of analysis tools, including probability models, graph theory, and computational algorithms, exposing students to ways of thinking about types of data that are different from typical statistical data. Concepts are demonstrated in the context of real applications, such as relationships between financial institutions, between genes or proteins, between neurons in the brain, and between terrorist groups. Methods and models described in detail include random graph models, percolation processes, methods for sampling from huge networks, network partitioning, and community detection. In addition to static networks the book introduces dynamic networks such as epidemics, where time is an important component.

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Acerca del autor

Alan J. Izenman is Professor of Statistical Science at Temple University. He received his Ph.D. from the University of California, Berkeley. He was a faculty member at Tel Aviv University and Colorado State University, and was a visiting faculty member at the University of Chicago, the University of Minnesota, and Stanford University. He was Program Director of Statistics and Probability at NSF (1992-94). A Fellow of the ASA, RSS, and ISI, he has served on the Editorial Boards of JASA, Law, Probability, and Risk, and Statistical Analysis and Data Mining. He is the author of Modern Multivariate Statistical Techniques (2013).

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Editorial
Cambridge University Press
Año de publicación
2023
Idioma
Inglés
ISBN 10 
1108835767
ISBN 13 
9781108835763
Encuadernación
Tapa dura
Número de páginas
550
Contacto del fabricante
no disponible
Persona responsable
gpsr@libri.de
gpsr@libri.de

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