A First Course in Network Science
Reduzierte Artikel in dieser Kategorie
| Verlag | Cambridge University Press |
| Auflage | 2020 |
| Seiten | 300 |
| Format | 19,5 x 25,2 x 1,8 cm |
| Gewicht | 800 g |
| Artikeltyp | Englisches Buch |
| EAN | 9781108471138 |
| Bestell-Nr | 10847113UA |
A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.
Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.
Inhaltsverzeichnis:
Preface; Introduction; 1. Network elements; 2. Small worlds; 3. Hubs; 4. Directions and weights; 5. Network models; 6. Communities; 7. Dynamics; Appendix A. Python tutorial; Appendix B. NetLogo models; Bibliography; Index.
Rezension:
'A First Course in Network Science by Menczer, Fortunato, and Davis is an easy-to-follow introduction into network science. An accessible text by some of the best-known practitioners of the field, offering a wonderful place to start one's journey into this fascinating field, and its potential applications.' Albert-László Barabási, Dodge Distinguished Professor of Network Science, Northeastern University
