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Einband grossArtificial Intelligence: Analytics, Platforms, and Risks
ISBN/GTIN

Artificial Intelligence: Analytics, Platforms, and Risks

BuchKartoniert, Paperback
195 Seiten
Englisch
Springererscheint am09.10.20242025
This companion volume to Artificial Intelligence for Everyone offers a comprehensive exploration of AI analytics, catering to individuals of all backgrounds and expertise levels. It seeks to demystify AI analytics by exploring core concepts, explaining various stages (descriptive, predictive, prescriptive), and highlighting their limitations. Through domain-specific applications, it illustrates how AI is utilized across industries for innovation and efficiency, providing dedicated subsections for healthcare, finance, customer support, and more.Artificial Intelligence: Analytics, Platforms, and Risks thoroughly examines the AI infrastructure and ecosystem, offering insights into frameworks, platforms, tools, key players, and the critical hardware and software components supporting AI applications. It also addresses the multifaceted risks and challenges of AI, such as bad data, model selection bias, job displacement, weaponization, and ethical dilemmas, along with strategies to mitigate these risks. Additionally, it discusses the hurdles in AI adoption, including roadblocks, myths, planning complexities, resource requirements, and data and model challenges. Looking ahead, the book explores the future of AI, highlighting catalysts for technological progress, the transformative impact across industries, and emerging trends shaping the field. With the aim of empowering readers to navigate the complexities of AI, harness its potential, and contribute to its responsible and ethical advancement, this book serves as a comprehensive guide to AI technologies.mehr

Produkt

KlappentextThis companion volume to Artificial Intelligence for Everyone offers a comprehensive exploration of AI analytics, catering to individuals of all backgrounds and expertise levels. It seeks to demystify AI analytics by exploring core concepts, explaining various stages (descriptive, predictive, prescriptive), and highlighting their limitations. Through domain-specific applications, it illustrates how AI is utilized across industries for innovation and efficiency, providing dedicated subsections for healthcare, finance, customer support, and more.Artificial Intelligence: Analytics, Platforms, and Risks thoroughly examines the AI infrastructure and ecosystem, offering insights into frameworks, platforms, tools, key players, and the critical hardware and software components supporting AI applications. It also addresses the multifaceted risks and challenges of AI, such as bad data, model selection bias, job displacement, weaponization, and ethical dilemmas, along with strategies to mitigate these risks. Additionally, it discusses the hurdles in AI adoption, including roadblocks, myths, planning complexities, resource requirements, and data and model challenges. Looking ahead, the book explores the future of AI, highlighting catalysts for technological progress, the transformative impact across industries, and emerging trends shaping the field. With the aim of empowering readers to navigate the complexities of AI, harness its potential, and contribute to its responsible and ethical advancement, this book serves as a comprehensive guide to AI technologies.
Details
ISBN/GTIN978-3-031-64391-0
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2024
Erscheinungsdatum09.10.2024
Auflage2025
Seiten195 Seiten
SpracheEnglisch
IllustrationenX, 195 p.
Artikel-Nr.56433000

Inhalt/Kritik

Inhaltsverzeichnis
Preface.- Analytics.- Analytics Stages.- AI Analytics.- AI Analytics Applications.- Frameworks, Platforms and Tools.- AI Platforms: Key Players.- AI Platform: Additional Key Players.- AI Infrastructure.- Risks.- Additional Risks.- Risk Mitigation.- Mitigation Additional Risks.- Challenges.- AI Future.- Appendix.mehr

Schlagworte

Autor

Arshad Khan is an accomplished analytics professional and adjunct professor. He has written 20 books covering topics in software, engineering, and business. Mr. Khan has lectured at nine universities, among them various University of California extensions (Berkeley, Santa Cruz/Silicon Valley, and San Diego), as well as Golden Gate University, Santa Clara University, and San Francisco Bay University. He holds a graduate degree in chemical engineering and an MBA.