Leveraging machine learning for operation assessment:
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Santa Monica, Calif.
RAND Corporation
[2022]
|
| Schriftenreihe: | Research reports
RR-4196-A |
| Links: | https://doi.org/10.7249/RR4196 |
| Umfang: | 1 Online-Ressource (xvii, 77 Seiten) |
| ISBN: | 197740443X 9781977404435 |
| DOI: | 10.7249/RR4196 |
Internformat
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Datensatz im Suchindex
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| isbn | 197740443X 9781977404435 |
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| spelling | Egel, Daniel Verfasser (DE-588)1140492683 aut Leveraging machine learning for operation assessment Daniel Egel, Ryan Andrew Brown, Linda Robinson [und drei weitere] Santa Monica, Calif. RAND Corporation [2022] 1 Online-Ressource (xvii, 77 Seiten) txt rdacontent c rdamedia cr rdacarrier Research reports RR-4196-A Brown, Ryan Andrew Verfasser aut Robinson, Linda Verfasser aut https://doi.org/10.7249/RR4196 Verlag kostenfrei Volltext |
| spellingShingle | Egel, Daniel Brown, Ryan Andrew Robinson, Linda Leveraging machine learning for operation assessment |
| title | Leveraging machine learning for operation assessment |
| title_auth | Leveraging machine learning for operation assessment |
| title_exact_search | Leveraging machine learning for operation assessment |
| title_full | Leveraging machine learning for operation assessment Daniel Egel, Ryan Andrew Brown, Linda Robinson [und drei weitere] |
| title_fullStr | Leveraging machine learning for operation assessment Daniel Egel, Ryan Andrew Brown, Linda Robinson [und drei weitere] |
| title_full_unstemmed | Leveraging machine learning for operation assessment Daniel Egel, Ryan Andrew Brown, Linda Robinson [und drei weitere] |
| title_short | Leveraging machine learning for operation assessment |
| title_sort | leveraging machine learning for operation assessment |
| url | https://doi.org/10.7249/RR4196 |
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