Deploying AI in the Enterprise: It Approaches for Design, Devops, Governance, Change Management, Blockchain, and Quantum Computing

Part I: Getting Started Chapter 1: AI Introduction Chapter 2: AI Historical Perspective Chapter 3: Key ML, DL and Decision Optimization Concepts Part II: AI Deployment Chapter 4: AI Information Architecture Chapter 5: From Data to Predictions to Optimal Actions Chapter 6: The Operationalization of AI Chapter 7: Design Thinking and DevOps in the AI Context Part III: AI in Context Chapter 8: Applying AI to Data Governance and MDM Chapter 9: AI and Governance Chapter 10: AI and Change Management Chapter 11: AI and Blockchain Chapter 12: AI and Quantum Computing Part IV: AI Limitations and Future Challenges Chapter 13: Limitations of AIChapter 14: In Summary and OnwardChapter 15: Appendix: Abbreviations

Author: Eberhard Hechler, Martin Oberhofer, Thomas Schaeck
Publisher: Apress
Published: 09/26/2020
Pages: 331
Binding Type: Paperback
Weight: 1.37lbs
Size: 10.00h x 7.00w x 0.75d
ISBN13: 9781484262054
ISBN10: 1484262050
BISAC Categories:
- Computers | Artificial Intelligence | General
- Science | Physics | Quantum Theory

About the Author
Eberhard Hechler is an Executive Architect at the IBM Germany R&D Lab. He is a member of the DB2 Analytics Accelerator development group and addresses the broader data and AI on IBM Z scope, including machine learning for z/OS. After two-and-a-half years at the IBM Kingston Lab in New York, he worked in software development, performance optimization, IT/solution architecture and design, open source (Hadoop and Spark) integration, and master data management. He is a member of the IBM Academy of Technology Leadership team, and co-authored the following books: Enterprise MDM, The Art of Enterprise Information Architecture, and Beyond Big Data.

Martin Oberhofer is an IBM Distinguished Engineer and Executive Architect. He is a technologist and engineering leader with deep expertise in master data management, data governance, data integration, metadata and reference data management, artificial intelligence, and machine learning. He is accomplished at translating customer needs into software solutions, and works collaboratively with globally distributed development, design, and management teams. He guides development teams using Agile and DevOps software development methods. He is an elected member of the IBM Academy of Technology and the TEC CR. He is a certified IBM Master Inventor with over 100 granted patents and numerous publications, including four books.

Thomas Schaeck is an IBM Distinguished Engineer at IBM Data and AI, leading Watson Studio on IBM Cloud (Cloud Pak for Data) Desktop and integration with other IBM offerings. Previously, he led architecture and technical strategy for IBM Connections, WebSphere Portal, and IBM OpenPages. He also led architecture and technical direction for WebSphere Portal Platform and development of the WebSphere Portal Foundation, initiated and led the portal standards Java Portlet API and OASIS WSRP and Apache open source reference implementations, and initiated and led the Web 2.0 initiative for WebSphere Portal.

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