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Data science for transporta self-stu...
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Fox, Charles.
Data science for transporta self-study guide with computer exercises /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Data science for transportby Charles Fox.
Reminder of title:
a self-study guide with computer exercises /
Author:
Fox, Charles.
Published:
Cham :Springer International Publishing :2018.
Description:
xvii, 185 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
TransportationData processing
Online resource:
https://doi.org/10.1007/978-3-319-72953-4
ISBN:
9783319729534$q(electronic bk.)
Data science for transporta self-study guide with computer exercises /
Fox, Charles.
Data science for transport
a self-study guide with computer exercises /[electronic resource] :by Charles Fox. - Cham :Springer International Publishing :2018. - xvii, 185 p. :ill., digital ;24 cm. - Springer textbooks in earth sciences, geography and environment,2510-1307. - Springer textbooks in earth sciences, geography and environment..
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.
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.
ISBN: 9783319729534$q(electronic bk.)
Standard No.: 10.1007/978-3-319-72953-4doiSubjects--Topical Terms:
854549
Transportation
--Data processing
LC Class. No.: HE147.6 / .F69 2018
Dewey Class. No.: 388.0285
Data science for transporta self-study guide with computer exercises /
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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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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.
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Earth and Environmental Science (Springer-11646)
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EB HE147.6 .F791 2018 2018
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https://doi.org/10.1007/978-3-319-72953-4
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