Data science and complex networks: real cases studies with Python
Material type:
TextPublication details: London Oxford University Press 2017 Description: 130 pISBN: 9780199639601Subject(s): Python (Computer program language) | System analysis | Big data | Computer networks | Data structures (Computer science) | Database managementDDC classification: 003.72 Summary: Description
This book provides a comprehensive yet short description of the basic concepts of Complex Network theory. In contrast to other books the authors present these concepts through real case studies. The application topics span from Foodwebs, to the Internet, the World Wide Web and the Social Networks, passing through the International Trade Web and Financial time series. The final part is devoted to definition and implementation of the most important network models.
The text provides information on the structure of the data and on the quality of available datasets. Furthermore it provides a series of codes to allow immediate implementation of what is theoretically described in the book. Readers already used to the concepts introduced in this book can learn the art of coding in Python by using the online material. To this purpose the authors have set up a dedicated website where readers can download and test the codes. The whole project is aimed as a learning tool for scientists and practitioners, enabling them to begin working instantly in the field of Complex Networks.
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
Book
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Indian Institute of Management LRC General Stacks | IT & Decisions Sciences | 003.72 CAL (Browse shelf(Opens below)) | 1 | Available | 001042 |
Table of Contents
1:Food Webs
2:International Trade Networks and World Trade Web
3:The Internet Network
4:World Wide Web, Wikipedia and Social Networks
5:Financial Networks
6:Modelling
Description
This book provides a comprehensive yet short description of the basic concepts of Complex Network theory. In contrast to other books the authors present these concepts through real case studies. The application topics span from Foodwebs, to the Internet, the World Wide Web and the Social Networks, passing through the International Trade Web and Financial time series. The final part is devoted to definition and implementation of the most important network models.
The text provides information on the structure of the data and on the quality of available datasets. Furthermore it provides a series of codes to allow immediate implementation of what is theoretically described in the book. Readers already used to the concepts introduced in this book can learn the art of coding in Python by using the online material. To this purpose the authors have set up a dedicated website where readers can download and test the codes. The whole project is aimed as a learning tool for scientists and practitioners, enabling them to begin working instantly in the field of Complex Networks.
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