Machine Learning for Materials Discovery: Numerical Recipes and Practical Applications
Gespeichert in:
Hauptverfasser: | , , |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cham
Springer International Publishing
2024
Cham Springer |
Ausgabe: | 1st ed. 2024 |
Schriftenreihe: | Machine Intelligence for Materials Science
|
Schlagworte: | |
Online-Zugang: | DE-91 DE-19 DE-703 DE-706 Volltext |
Beschreibung: | 1 Online-Ressource (XX, 279 p. 110 illus., 95 illus. in color) |
ISBN: | 9783031446221 |
ISSN: | 2948-1821 |
DOI: | 10.1007/978-3-031-44622-1 |
Internformat
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Datensatz im Suchindex
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adam_text | |
any_adam_object | |
author | Krishnan, N. M. Anoop Kodamana, Hariprasad Bhattoo, Ravinder |
author_facet | Krishnan, N. M. Anoop Kodamana, Hariprasad Bhattoo, Ravinder |
author_role | aut aut aut |
author_sort | Krishnan, N. M. Anoop |
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discipline | Physik |
doi_str_mv | 10.1007/978-3-031-44622-1 |
edition | 1st ed. 2024 |
format | Electronic eBook |
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id | DE-604.BV049725619 |
illustrated | Not Illustrated |
indexdate | 2024-07-20T07:34:54Z |
institution | BVB |
isbn | 9783031446221 |
issn | 2948-1821 |
language | English |
oclc_num | 1437841073 |
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owner | DE-91 DE-BY-TUM DE-19 DE-BY-UBM DE-706 DE-703 |
owner_facet | DE-91 DE-BY-TUM DE-19 DE-BY-UBM DE-706 DE-703 |
physical | 1 Online-Ressource (XX, 279 p. 110 illus., 95 illus. in color) |
psigel | ZDB-2-PHA ZDB-2-PHA_2024 |
publishDate | 2024 |
publishDateSearch | 2024 |
publishDateSort | 2024 |
publisher | Springer International Publishing Springer |
record_format | marc |
series2 | Machine Intelligence for Materials Science |
spelling | Krishnan, N. M. Anoop Verfasser aut Machine Learning for Materials Discovery Numerical Recipes and Practical Applications by N. M. Anoop Krishnan, Hariprasad Kodamana, Ravinder Bhattoo 1st ed. 2024 Cham Springer International Publishing 2024 Cham Springer 1 Online-Ressource (XX, 279 p. 110 illus., 95 illus. in color) txt rdacontent c rdamedia cr rdacarrier Machine Intelligence for Materials Science 2948-1821 Computational Materials Science Machine Learning Complex Systems Theoretical, Mathematical and Computational Physics Ceramics Materials science / Data processing Machine learning System theory Mathematical physics Ceramic materials Kodamana, Hariprasad aut Bhattoo, Ravinder aut Erscheint auch als Druck-Ausgabe 978-3-031-44621-4 Erscheint auch als Druck-Ausgabe 978-3-031-44623-8 Erscheint auch als Druck-Ausgabe 978-3-031-44624-5 https://doi.org/10.1007/978-3-031-44622-1 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Krishnan, N. M. Anoop Kodamana, Hariprasad Bhattoo, Ravinder Machine Learning for Materials Discovery Numerical Recipes and Practical Applications Computational Materials Science Machine Learning Complex Systems Theoretical, Mathematical and Computational Physics Ceramics Materials science / Data processing Machine learning System theory Mathematical physics Ceramic materials |
title | Machine Learning for Materials Discovery Numerical Recipes and Practical Applications |
title_auth | Machine Learning for Materials Discovery Numerical Recipes and Practical Applications |
title_exact_search | Machine Learning for Materials Discovery Numerical Recipes and Practical Applications |
title_full | Machine Learning for Materials Discovery Numerical Recipes and Practical Applications by N. M. Anoop Krishnan, Hariprasad Kodamana, Ravinder Bhattoo |
title_fullStr | Machine Learning for Materials Discovery Numerical Recipes and Practical Applications by N. M. Anoop Krishnan, Hariprasad Kodamana, Ravinder Bhattoo |
title_full_unstemmed | Machine Learning for Materials Discovery Numerical Recipes and Practical Applications by N. M. Anoop Krishnan, Hariprasad Kodamana, Ravinder Bhattoo |
title_short | Machine Learning for Materials Discovery |
title_sort | machine learning for materials discovery numerical recipes and practical applications |
title_sub | Numerical Recipes and Practical Applications |
topic | Computational Materials Science Machine Learning Complex Systems Theoretical, Mathematical and Computational Physics Ceramics Materials science / Data processing Machine learning System theory Mathematical physics Ceramic materials |
topic_facet | Computational Materials Science Machine Learning Complex Systems Theoretical, Mathematical and Computational Physics Ceramics Materials science / Data processing Machine learning System theory Mathematical physics Ceramic materials |
url | https://doi.org/10.1007/978-3-031-44622-1 |
work_keys_str_mv | AT krishnannmanoop machinelearningformaterialsdiscoverynumericalrecipesandpracticalapplications AT kodamanahariprasad machinelearningformaterialsdiscoverynumericalrecipesandpracticalapplications AT bhattooravinder machinelearningformaterialsdiscoverynumericalrecipesandpracticalapplications |