Causal artifical intelligence

• Verfasst von: Hurwitz, Judith [VerfasserIn]
• Verfasst von: Thompson, John K. [VerfasserIn]
• Titel: Causal artifical intelligence
• Titelzusatz: the next step in effective business AI
• Verf.angabe: Judith S. Hurwitz, John K. Thompson
• Verlagsort: Hoboken, NJ
• Verlag: Wiley
• E-Jahr: 2024
• Jahr: [2024]
• Umfang: 1 online resource
• Fussnoten: Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on September 11, 2023)
• ISBN: 978-1-394-18414-9
• ISBN: 1-394-18414-X
• ISBN: 978-1-394-18415-6
• ISBN: 1-394-18415-8
• ISBN: 978-1-394-18413-2
• Datenträger: Online-Ressource
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe
• Sach-SW: Raisonnement qualitatif
• K10plus-PPN: 186880867X
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m439987211X
• Lokale URL Inst.: Zum Volltext

Abstract

Discover the next major revolution in data science and AI and how it applies to your organization In Causal Artificial Intelligence: The Next Step in Effective, Efficient, and Practical AI, a team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI. The book's discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings. Useful for both data scientists and business-side professionals, the book offers: Clear and compelling descriptions of the concept of causality and how it can benefit your organization Detailed use cases and examples that vividly demonstrate the value of causality for solving business problems Useful strategies for deciding when to use correlation-based approaches and when to use causal inference An enlightening and easy-to-understand treatment of an essential business topic, Causal Artificial Intelligence is a must-read for data scientists, subject matter experts, and business leaders seeking to familiarize themselves with a rapidly growing area of AI application and research.