Actuarial Data Science : : Maschinelles Lernen in der Versicherung / / Martin Seehafer, Stefan Nörtemann, Jonas Offtermatt, Fabian Transchel, Axel Kiermaier, René Külheim, Wiltrud Weidner.
Actuaries, business mathematicians and IT specialists in corresponding companies are increasingly confronted with new requirements in the areas of IT automation, data management, machine learning / AI and data security, which are not covered by their previous basic mathematical and scientific traini...
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| Superior document: | Title is part of eBook package: De Gruyter DG Plus DeG Package 2021 Part 1 |
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| VerfasserIn: | |
| Place / Publishing House: | Berlin ;, Boston : : De Gruyter, , [2021] ©2021 |
| Year of Publication: | 2021 |
| Language: | German |
| Series: | De Gruyter STEM
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| Online Access: | |
| Physical Description: | 1 online resource (X, 370 p.) |
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Table of Contents:
- Frontmatter
- Vorwort
- Inhalt
- 1 Actuarial Data Science – Business Cases
- 2 Crashkurs in Data Mining Anwendungen
- 3 Neue Versicherungsprodukte
- 4 Tools, Sprachen, Frameworks
- 5 Informationstechnologie
- 6 Mathematische Verfahren
- 7 Korrelation und kausale Inferenz
- 8 Data Mining
- 9 Gesellschaftliches Umfeld
- A Appendix
- Nachwort & Danksagungen
- Literatur
- Stichwortverzeichnis