Data Science for Transport A Self-Study Guide with Computer Exercises / by Charles Fox.
This book offers a unique introduction to the application of data science for transport professionals and students of transport studies. Based on a course taught by the Leeds Institute for Transport Studies, the world’s leading center for training transport professionals, it represents the first tex...
Springer International Publishing : Imprint: Springer,
|Edition:||1st ed. 2018.|
|Series:||Springer Textbooks in Earth Sciences, Geography and Environment,
Springer eBook Collection.
|Online Access:||Click to view e-book|
|Holy Cross Note:||Loaded electronically.|
Electronic access restricted to members of the Holy Cross Community.
|Summary:||This book offers a unique introduction to the application of data science for transport professionals and students of transport studies. Based on a course taught by the Leeds Institute for Transport Studies, the world’s leading center for training transport professionals, it represents the first textbook in this new area. As transportation planning has become increasingly data-driven, all graduate students and transport professionals urgently need to update their skills to include databases, machine learning, Bayesian statistics, geographic information system (GIS), and big data tools. Similarly, transport professionals including national and local government planners, transport consultants, and car company engineers are called upon to integrate these disparate areas with a specific focus on transportation issues, such as maps. The textbook also features a downloadable software package with all of the open source tools and libraries used in code examples throughout the book, including Python, Spyder, PostGIS, PyMC and GPy installations. As such, it offers a unique resource for graduate/advanced undergraduate students and instructors in transportation studies, urban and regional planning, engineering and geography, as well as transportation professionals.|
|Physical Description:||XVII, 185 p. 77 illus., 49 illus. in color. online resource.|