Machine learning for credit risk analytics:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin
[2022?]
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Date of Colloquium: 24.03.2022 Der Text enthält eine Zusammenfassung in deutscher und englischer Sprache. |
| Beschreibung: | xviii, 174 Seiten Illustrationen, Diagramme |
Internformat
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| 245 | 1 | 0 | |a Machine learning for credit risk analytics |c by Nikita Kozodoi, M.Sc. |
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| 502 | |b Dissertation |c Humboldt-Universität zu Berlin |d 2022 | ||
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Datensatz im Suchindex
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| spelling | Kozodoi, Nikita Verfasser (DE-588)1259098109 aut Machine learning for credit risk analytics by Nikita Kozodoi, M.Sc. Berlin [2022?] xviii, 174 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Date of Colloquium: 24.03.2022 Der Text enthält eine Zusammenfassung in deutscher und englischer Sprache. Dissertation Humboldt-Universität zu Berlin 2022 (DE-588)4113937-9 Hochschulschrift gnd-content Erscheint auch als Online-Ausgabe Kozodoi, Nikita Machine learning for credit risk analytics urn:nbn:de:kobv:11-110-18452/25386-6 10.18452/24444 (DE-604)BV048255024 http://edoc.hu-berlin.de/18452/25386 Verlag kostenfrei Volltext |
| spellingShingle | Kozodoi, Nikita Machine learning for credit risk analytics |
| subject_GND | (DE-588)4113937-9 |
| title | Machine learning for credit risk analytics |
| title_auth | Machine learning for credit risk analytics |
| title_exact_search | Machine learning for credit risk analytics |
| title_exact_search_txtP | Machine learning for credit risk analytics |
| title_full | Machine learning for credit risk analytics by Nikita Kozodoi, M.Sc. |
| title_fullStr | Machine learning for credit risk analytics by Nikita Kozodoi, M.Sc. |
| title_full_unstemmed | Machine learning for credit risk analytics by Nikita Kozodoi, M.Sc. |
| title_short | Machine learning for credit risk analytics |
| title_sort | machine learning for credit risk analytics |
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| url | http://edoc.hu-berlin.de/18452/25386 |
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