Machine learning for civil & environmental engineers: a practical approach to data-driven analysis, explainability, and causality
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, New Jersey
Wiley
2023
|
| Ausgabe: | 1st ed |
| Schlagworte: | |
| Online-Zugang: | DE-91 |
| Beschreibung: | 1 Online-Ressource (xix, 588 Seiten) Illustrationen, Diagramme |
| ISBN: | 9781119897620 |
Internformat
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Datensatz im Suchindex
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| edition | 1st ed |
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| id | DE-604.BV049433128 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:10:36Z |
| indexdate | 2024-07-20T04:47:04Z |
| institution | BVB |
| isbn | 9781119897620 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034779214 |
| oclc_num | 1390560489 |
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| physical | 1 Online-Ressource (xix, 588 Seiten) Illustrationen, Diagramme |
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| publishDate | 2023 |
| publishDateSearch | 2023 |
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| publisher | Wiley |
| record_format | marc |
| spelling | Naser, M. Z. Verfasser aut Machine learning for civil & environmental engineers a practical approach to data-driven analysis, explainability, and causality M.Z. Naser Machine learning for civil and environmental engineers Hoboken, New Jersey Wiley 2023 © 2023 1 Online-Ressource (xix, 588 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Machine learning Civil engineering-Data processing Bautechnik (DE-588)4004955-3 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 s Bautechnik (DE-588)4004955-3 s DE-604 Erscheint auch als Naser, M. Z. Machine Learning for Civil and Environmental Engineers Newark : John Wiley & Sons, Incorporated,c2023 Druck-Ausgabe, Hardcover 978-1-119-89760-6 |
| spellingShingle | Naser, M. Z. Machine learning for civil & environmental engineers a practical approach to data-driven analysis, explainability, and causality Machine learning Civil engineering-Data processing Bautechnik (DE-588)4004955-3 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4004955-3 (DE-588)4193754-5 |
| title | Machine learning for civil & environmental engineers a practical approach to data-driven analysis, explainability, and causality |
| title_alt | Machine learning for civil and environmental engineers |
| title_auth | Machine learning for civil & environmental engineers a practical approach to data-driven analysis, explainability, and causality |
| title_exact_search | Machine learning for civil & environmental engineers a practical approach to data-driven analysis, explainability, and causality |
| title_exact_search_txtP | Machine Learning for Civil and Environmental Engineers A Practical Approach to Data-Driven Analysis, Explainability, and Causality |
| title_full | Machine learning for civil & environmental engineers a practical approach to data-driven analysis, explainability, and causality M.Z. Naser |
| title_fullStr | Machine learning for civil & environmental engineers a practical approach to data-driven analysis, explainability, and causality M.Z. Naser |
| title_full_unstemmed | Machine learning for civil & environmental engineers a practical approach to data-driven analysis, explainability, and causality M.Z. Naser |
| title_short | Machine learning for civil & environmental engineers |
| title_sort | machine learning for civil environmental engineers a practical approach to data driven analysis explainability and causality |
| title_sub | a practical approach to data-driven analysis, explainability, and causality |
| topic | Machine learning Civil engineering-Data processing Bautechnik (DE-588)4004955-3 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Machine learning Civil engineering-Data processing Bautechnik Maschinelles Lernen |
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