1.

Record Nr.

UNINA9910299390903321

Autore

Fox Charles

Titolo

Data Science for Transport : A Self-Study Guide with Computer Exercises / / by Charles Fox

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018

ISBN

3-319-72953-5

Edizione

[1st ed. 2018.]

Descrizione fisica

1 online resource (XVII, 185 p. 77 illus., 49 illus. in color.)

Collana

Springer Textbooks in Earth Sciences, Geography and Environment, , 2510-1307

Disciplina

307.12

Soggetti

Regional planning

City planning

Transportation engineering

Traffic engineering

Statistics

Computers

Regional economics

Space in economics

Landscape/Regional and Urban Planning

Transportation Technology and Traffic Engineering

Statistics and Computing/Statistics Programs

Information Systems and Communication Service

Regional/Spatial Science

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Preface/ Foreword (professional public transport analyst -- Introduction -- What is Data Science? -- Introduction to Python programming -- Database Design -- Data Munging -- Spatial Data -- Bayesian Interference -- Discriminative Classification -- Spatial Analysis -- Data Visualisation -- Database Scaling -- Professional Issues -- Appendix -- Index.

Sommario/riassunto

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.