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Demystifying Artificial Intelligence

Symbolic, Data-Driven, Statistical and Ethical AI

dc.contributor.editorGillain, Emmanuel
dc.date.accessioned2025-03-07T22:57:42Z
dc.date.available2025-03-07T22:57:42Z
dc.date.issued2024
dc.date.submitted2024-11-06T10:37:23Z
dc.identifierONIX_20241106_9783111426143_32
dc.identifierhttps://library.oapen.org/handle/20.500.12657/94293
dc.identifier.urihttps://doab-dev.siscern.org/handle/20.500.12854/170131
dc.description.abstractThe book provides an overview of the different AI technologies, demystifying terms such as search, reasoning, learning, adapting, understanding, and interacting. It covers the two dominant paradigms in AI, both the “data-driven” and “symbolic” AI systems, showing how they can complement each other. The theory is illustrated with 22 real-world examples from industry, giving a solid understanding of AI concepts, applicability, and limitations.
dc.languageEnglish
dc.relation.ispartofseriesDe Gruyter STEM
dc.rightsopen access
dc.subject.otherMachine Learning
dc.subject.otherNatural Language Processing
dc.subject.otherNeural Networks
dc.subject.otherLogic Reasoning
dc.subject.otherthema EDItEUR::U Computing and Information Technology::UB Information technology: general topics
dc.subject.otherthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
dc.subject.otherthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
dc.subject.otherthema EDItEUR::U Computing and Information Technology::UY Computer science::UYZ Human–computer interaction
dc.titleDemystifying Artificial Intelligence
dc.title.alternativeSymbolic, Data-Driven, Statistical and Ethical AI
dc.typebook
oapen.identifier.doi10.1515/978311142614
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oapen.relation.isbn9783111426143
oapen.relation.isbn9783111425672
oapen.relation.isbn9783111426303
oapen.imprintDe Gruyter
oapen.pages460
oapen.place.publicationBerlin/Boston
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