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Working With Network Data : A Data Science Perspective, Hardcover by Bagrow, ...

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Specifiche dell'oggetto

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Come Nuovo: Libro che sembra nuovo anche se è già stato letto. La copertina non presenta segni di ...
ISBN
9781009212595

Informazioni su questo prodotto

Product Identifiers

Publisher
Cambridge University Press
ISBN-10
1009212591
ISBN-13
9781009212595
eBay Product ID (ePID)
2336606939

Product Key Features

Book Title
Working with Network Data
Number of Pages
400 Pages
Language
English
Publication Year
2024
Topic
Engineering (General), Physics / Mathematical & Computational
Illustrator
Yes
Genre
Technology & Engineering, Science
Author
James Bagrow, Yong‐Yeol Ahn
Format
Hardcover

Dimensions

Item Height
1.4 in
Item Length
9.9 in
Item Width
7 in

Additional Product Features

LCCN
2023-054233
Dewey Edition
23/eng/20240508
Reviews
'An essential resource for newcomers to network science, this book expertly addresses the practical challenges of handling network data. Through a rich array of real-world examples and hands-on exercises, Bagrow and Ahn skillfully guide readers through the complexities of conceptualizing and analyzing networked data, making this text a fundamental tool for students and researchers eager to explore the power of connections across various disciplines.' Albert-László Barabási, Dodge Distinguished Professor of Network Science at Northeastern University
Dewey Decimal
004.6/5
Table Of Content
Contents; Preface; Part I. Background: 1. A whirlwind tour of network science; 2. Network data across fields; 3. Data ethics; 4. Primer; Part II. Applications, Tools and Tasks: 5. The life-cycle of a network study; 6. Gathering data; 7. Extracting networks from data - the 'upstream task'; 8. Implementation: storing and manipulating network data; 9. Incorporating node and edge attributes; 10. Awful errors and how to amend them; 11. Explore and explain: statistics for network data; 12. Understanding network structure and organization; 13. Visualizing networks; 14. Summarizing and comparing networks; 15. Dynamics and dynamic networks; 16. Machine learning; Interlude - Good practices for scientific computing; 17. Research record-keeping; 18. Data provenance; 19. Reproducible and reliable code; 20. Helpful tools; Part III. Fundamentals: 21. Networks demand network thinking: the friendship paradox; 22. Network models; 23. Statistical models and inference; 24. Uncertainty quantification and error analysis; 25. Ghost in the matrix: spectral methods for networks; 26. Embedding and machine learning; 27. Big data and scalability; Conclusion; Bibliography; Index.
Synopsis
Drawing examples from real-world networks, this essential book traces the methods behind network analysis and equips you with a toolbox of diverse methods and data modelling approaches. Suitable for both graduate students and researchers across a range of disciplines, this novel text provides a fast-track to network data expertise., 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.
LC Classification Number
TK5105.5.B3 2024

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