Working with Network Data: A Data Science Perspective
Author: James Bagrow (Author), Yong‐Yeol Ahn (Author)
Publisher finelybook 出版社: Cambridge University Press
Edition 版次: New
Publication Date 出版日期: 2024-06-13
Language 语言: English
Print Length 页数: 554 pages
ISBN-10: 1009212591
ISBN-13: 9781009212595
Book Description
By finelybook
Drawing examples from real-world networks, this essential book traces the methods behind network analysis and explains how network data is first gathered, then processed and interpreted. The text will equip you with a toolbox of diverse methods and data modelling approaches, allowing you to quickly start making your own calculations on a huge variety of networked systems. This book sets you up to succeed, addressing the questions of what you need to know and what to do with it, when beginning to work with network data. The hands-on approach adopted throughout means that beginners quickly become capable practitioners, guided by a wealth of interesting examples that demonstrate key concepts. Exercises using real-world data extend and deepen your understanding, and develop effective working patterns in network calculations and analysis. Suitable for both graduate students and researchers across a range of disciplines, this novel text provides a fast-track to network data expertise.
Book Description
By finelybook
Suitable for students and researchers in a range of disciplines, this novel text provides a fast-track to network data expertise.
About the Author
James Bagrow is Associate Professor in Mathematics & Statistics at the University of Vermont. He works at the intersection of data science, complex systems and applied mathematics, using cutting-edge methods, mathematical models and large-scale data to explore and understand complex networks and systems.
Yong-Yeol Ahn is Professor at Indiana University and a former Visiting Professor at the Massachusetts Institute of Technology. He specializes in network and data science and machine learning, and his research on complex social and biological systems has been recognized by many awards, including the Microsoft Research Faculty Fellowship.
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