| 书目名称 | Data Science for Transport | | 副标题 | A Self-Study Guide w | | 编辑 | Charles Fox | | 视频video | | | 概述 | Introduces data science for students of transport studies, geography and the geosciences, as well as transport professionals.The only book to integrate the whole stack of transport data analysis.Addre | | 丛书名称 | Springer Textbooks in Earth Sciences, Geography and Environment | | 图书封面 |  | | 描述 | The quantity, diversity and availability of transport data is increasing rapidly, requiring new skills in the management and interrogation of data and databases. Recent years have seen a new wave of ‘big data‘, ‘Data Science‘, and ‘smart cities‘ changing the world, with the Harvard Business Review describing Data Science as the "sexiest job of the 21st century". Transportation professionals and researchers need to be able to use data and databases in order to establish quantitative, empirical facts, and to validate and challenge their mathematical models, whose axioms have traditionally often been assumed rather than rigorously tested against data. This book takes a highly practical approach to learning about Data Science tools and their application to investigating transport issues. The focus is principally on practical, professional work with real data and tools, including business and ethical issues..".Transport modeling practice was developed in a data poor world, and many of our current techniques and skills are building on that sparsity. In a new data rich world, the required tools are different and the ethical questions around data and privacy are definitely different. I am | | 出版日期 | Textbook 2018 | | 关键词 | Quantitative Geography; Transport Studies; Data Science for Geography and Geoscience; Machine Learning | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-72953-4 | | isbn_softcover | 978-3-030-10291-3 | | isbn_ebook | 978-3-319-72953-4Series ISSN 2510-1307 Series E-ISSN 2510-1315 | | issn_series | 2510-1307 | | copyright | Springer International Publishing AG 2018 |
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发表于 2025-3-21 17:51:26
