IBM Power Systems Enterprise AI solutions /

This IBM® Redpaper publication helps the line of business (LOB), data science, and information technology (IT) teams develop an information architecture (IA) for their enterprise artificial intelligence (AI) environment. It describes the challenges that are faced by the three roles when creating and...

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Détails bibliographiques
Cote:Libro Electrónico
Auteurs principaux: Corneau, Glen (Auteur), Laidlaw, Andrew (Auteur), Quezada, Marcos (Auteur)
Format: Électronique eBook
Langue:Inglés
Publié: Poughkeepsie, NY : IBM Corporation, IBM Redbooks, 2019.
Édition:First edition (September 2019).
Collection:IBM redpaper.
Sujets:
IBM Power systems.
IBM Power systems
Artificial intelligence > Industrial applications.
Big data > Industrial applications.
Information visualization.
Intelligence artificielle > Applications industrielles.
Données volumineuses > Applications industrielles.
Visualisation de l'information.
Artificial intelligence > Industrial applications
Information visualization
Accès en ligne:Texto completo (Requiere registro previo con correo institucional)
Description
Résumé:This IBM® Redpaper publication helps the line of business (LOB), data science, and information technology (IT) teams develop an information architecture (IA) for their enterprise artificial intelligence (AI) environment. It describes the challenges that are faced by the three roles when creating and deploying enterprise AI solutions, and how they can collaborate for best results. This publication also highlights the capabilities of the IBM Cognitive Systems and AI solutions: IBM Watson® Machine Learning Community Edition IBM Watson Machine Learning Accelerator (WMLA) IBM PowerAI Vision IBM Watson Machine Learning IBM Watson Studio Local IBM Video Analytics H2O Driverless AI IBM Spectrum® Scale IBM Spectrum Discover This publication examines the challenges through five different use case examples: Artificial vision Natural language processing (NLP) Planning for the future Machine learning (ML) AI teaming and collaboration This publication targets readers from LOBs, data science teams, and IT departments, and anyone that is interested in understanding how to build an IA to support enterprise AI development and deployment.
Description:Number on back cover: REDP-5556-00.
Description matérielle:1 online resource (1 volume) : illustrations
Bibliographie:Includes bibliographical references.

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