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| |  Online-Ressource |
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| Verfasst von: | Redman, Thomas C. [VerfasserIn]  |
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| | Hoerl, Roger Wesley [VerfasserIn] |
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| Titel: | AI and statistics |
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| Titelzusatz: | perfect together |
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| Verf.angabe: | Thomas C. Redman, Roger W. Hoerl |
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| Ausgabe: | [First edition]. |
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| Verlagsort: | [Cambridge, Massachusetts] |
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| Verlag: | MIT Sloan Management Review |
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| E-Jahr: | 2024 |
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| Jahr: | [2024] |
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| Umfang: | 1 online resource (6 pages) |
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| Fussnoten: | Reprint #65413 |
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| Abstract: | Today’s AI developers struggle to predict which algorithms will work. AI lacks a basis for inference: a solid foundation on which to base predictions and decisions. This makes AI tough to explain, creates mistrust, and dooms many AI models to fail in deployment. However, help for AI teams and projects is available from an unlikely source: classical statistics. This article explains how business leaders can apply statistical methods and engage statistics experts to improve results. |
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| URL: | Aggregator: https://learning.oreilly.com/library/view/-/53863MIT65413/?ar |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | Intelligence artificielle |
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| | Statistique |
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| | artificial intelligence |
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| | statistics |
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| K10plus-PPN: | 189048234X |
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| Lokale URL UB: |  Zum Volltext |
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| | Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg |
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| |  Bestellen/Vormerken für Benutzer des Klinikums Mannheim
Eigene Kennung erforderlich |
| Bibliothek/Idn: | UW / m4533698948 |
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| Lokale URL Inst.: | Zum Volltext |
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AI and statistics / Redman, Thomas C. [VerfasserIn]; [2024] (Online-Ressource)
69219139
