Data science for transport : a self-study guide with computer exercises.
Fox, Charles.
2018
HE147.6
Available Online

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Title Data science for transport : a self-study guide with computer exercises.
Author Fox, Charles.
ISBN 9783319729534 (electronic book)
3319729535 (electronic book)
9783319729527
3319729527
DOI https://doi.org/10.1007/978-3-319-72953-4
Imprint [S.l.] : Springer, 2018.
Language English
Description 1 online resource.
Other Standard Identifiers 10.1007/978-3-319-72953-4 doi
Call Number HE147.6
Dewey Decimal Classification 388.0285
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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Series Springer textbooks in earth sciences, geography and environment.
Available in Other Form Print version: 9783319729527
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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.

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