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Published by The Institution of Engineering and Technology, 2023
ISBN 10: 1839537019 ISBN 13: 9781839537011
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Published by Cambridge University Press, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Published by Cambridge University Press, 2026
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Published by Cambridge University Press, GB, 2026
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Hardback. Condition: New. Knowledge-infused learning directly confronts the opacity of current 'black-box' AI models by combining data-driven machine learning techniques with the structured insights of symbolic AI. This guidebook introduces the pioneering techniques of neurosymbolic AI, which blends statistical models with symbolic knowledge to make AI safer and user-explainable. This is critical in high-stakes AI applications in healthcare, law, finance, and crisis management. The book brings readers up to speed on advancements in statistical AI, including transformer models such as BERT and GPT, and provides a comprehensive overview of weakly supervised, distantly supervised, and unsupervised learning methods alongside their knowledge-enhanced variants. Other topics include active learning, zero-shot learning, and model fusion. Beyond theory, the book presents practical considerations and applications of neurosymbolic AI in conversational systems, mental health, crisis management systems, and social and behavioral sciences, making it a pragmatic reference for AI system designers in academia and industry.
Language: English
Published by Cambridge University Press, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Published by Cambridge University Press, GB, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Hardback. Condition: New. Knowledge-infused learning directly confronts the opacity of current 'black-box' AI models by combining data-driven machine learning techniques with the structured insights of symbolic AI. This guidebook introduces the pioneering techniques of neurosymbolic AI, which blends statistical models with symbolic knowledge to make AI safer and user-explainable. This is critical in high-stakes AI applications in healthcare, law, finance, and crisis management. The book brings readers up to speed on advancements in statistical AI, including transformer models such as BERT and GPT, and provides a comprehensive overview of weakly supervised, distantly supervised, and unsupervised learning methods alongside their knowledge-enhanced variants. Other topics include active learning, zero-shot learning, and model fusion. Beyond theory, the book presents practical considerations and applications of neurosymbolic AI in conversational systems, mental health, crisis management systems, and social and behavioral sciences, making it a pragmatic reference for AI system designers in academia and industry.
Language: English
Published by Cambridge University Press, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Published by Cambridge University Press, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Published by Cambridge University Press, Cambridge, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Hardcover. Condition: new. Hardcover. Knowledge-infused learning directly confronts the opacity of current 'black-box' AI models by combining data-driven machine learning techniques with the structured insights of symbolic AI. This guidebook introduces the pioneering techniques of neurosymbolic AI, which blends statistical models with symbolic knowledge to make AI safer and user-explainable. This is critical in high-stakes AI applications in healthcare, law, finance, and crisis management. The book brings readers up to speed on advancements in statistical AI, including transformer models such as BERT and GPT, and provides a comprehensive overview of weakly supervised, distantly supervised, and unsupervised learning methods alongside their knowledge-enhanced variants. Other topics include active learning, zero-shot learning, and model fusion. Beyond theory, the book presents practical considerations and applications of neurosymbolic AI in conversational systems, mental health, crisis management systems, and social and behavioral sciences, making it a pragmatic reference for AI system designers in academia and industry. This practical guidebook introduces an emerging field that confronts the opacity of current 'black-box' AI models. Knowledge-infused learning combines machine learning and symbolic AI to make AI safer and more explainable, which is vital for applications in human-critical contexts such as healthcare, law, and finance. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Language: English
Published by The Institution of Engineering and Technology, 2023
ISBN 10: 1839537019 ISBN 13: 9781839537011
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Language: English
Published by Cambridge University Press, GB, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Hardback. Condition: New. Knowledge-infused learning directly confronts the opacity of current 'black-box' AI models by combining data-driven machine learning techniques with the structured insights of symbolic AI. This guidebook introduces the pioneering techniques of neurosymbolic AI, which blends statistical models with symbolic knowledge to make AI safer and user-explainable. This is critical in high-stakes AI applications in healthcare, law, finance, and crisis management. The book brings readers up to speed on advancements in statistical AI, including transformer models such as BERT and GPT, and provides a comprehensive overview of weakly supervised, distantly supervised, and unsupervised learning methods alongside their knowledge-enhanced variants. Other topics include active learning, zero-shot learning, and model fusion. Beyond theory, the book presents practical considerations and applications of neurosymbolic AI in conversational systems, mental health, crisis management systems, and social and behavioral sciences, making it a pragmatic reference for AI system designers in academia and industry.
Language: English
Published by Cambridge University Press, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Knowledge-infused learning directly confronts the opacity of current 'black-box' AI models by combining data-driven machine learning techniques with the structured insights of symbolic AI. This guidebook introduces the pioneering techniques of neurosymbolic AI, which blends statistical models with symbolic knowledge to make AI safer and user-explainable. This is critical in high-stakes AI applications in healthcare, law, finance, and crisis management. The book brings readers up to speed on advancements in statistical AI, including transformer models such as BERT and GPT, and provides a comprehensive overview of weakly supervised, distantly supervised, and unsupervised learning methods alongside their knowledge-enhanced variants. Other topics include active learning, zero-shot learning, and model fusion. Beyond theory, the book presents practical considerations and applications of neurosymbolic AI in conversational systems, mental health, crisis management systems, and social and behavioral sciences, making it a pragmatic reference for AI system designers in academia and industry.
Language: English
Published by The Institution of Engineering and Technology, 2023
ISBN 10: 1839537019 ISBN 13: 9781839537011
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
£ 113.21
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Language: English
Published by Institution of Engineering & Technology, 2023
ISBN 10: 1839537019 ISBN 13: 9781839537011
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 360 | Sprache: Englisch | Produktart: Bücher | Personal knowledge graphs (PKGs) support the development of innovative digitalized personalized applications, which keep users updated, help them manage their day-to-day activities and facilitate informed decisions. This book systematically explores the global advanced research around PKGs from methodologies to tools and applications.
Language: English
Published by The Institution of Engineering and Technology, 2023
ISBN 10: 1839537019 ISBN 13: 9781839537011
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Language: English
Published by Cambridge University Press, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Language: English
Published by Cambridge University Press, GB, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
Seller: Rarewaves.com UK, London, United Kingdom
Hardback. Condition: New. Knowledge-infused learning directly confronts the opacity of current 'black-box' AI models by combining data-driven machine learning techniques with the structured insights of symbolic AI. This guidebook introduces the pioneering techniques of neurosymbolic AI, which blends statistical models with symbolic knowledge to make AI safer and user-explainable. This is critical in high-stakes AI applications in healthcare, law, finance, and crisis management. The book brings readers up to speed on advancements in statistical AI, including transformer models such as BERT and GPT, and provides a comprehensive overview of weakly supervised, distantly supervised, and unsupervised learning methods alongside their knowledge-enhanced variants. Other topics include active learning, zero-shot learning, and model fusion. Beyond theory, the book presents practical considerations and applications of neurosymbolic AI in conversational systems, mental health, crisis management systems, and social and behavioral sciences, making it a pragmatic reference for AI system designers in academia and industry.
Language: English
Published by The Institution of Engineering and Technology, 2023
ISBN 10: 1839537019 ISBN 13: 9781839537011
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Language: English
Published by Inst of Engineering & Technology, 2023
ISBN 10: 1839537019 ISBN 13: 9781839537011
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Language: English
Published by Cambridge University Press, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
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Language: English
Published by Institution Of Engineering & Technology Nov 2023, 2023
ISBN 10: 1839537019 ISBN 13: 9781839537011
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Neuware - Since the development of the semantic web, knowledge graphs (KGs) have been used by search engines, knowledge-engines and question-answering services as well as social networks. A knowledge graph, also known as a semantic network, represents and illustrates a network of real-world entities such as objects, events, situations, or concepts and the relationships between them. This information is usually stored in a graph database and visualized as a graph structure, prompting the term 'knowledge graph'. Knowledge graphs structure the information of entities, their properties and the relation between them. Personal knowledge graphs (PKG) encode the same information at an individual level and therefore vary widely. PKGs require the processing of each person's individual information and is constructed in an automated fashion. Once a PKG is constructed, it will be integrated in broader purpose KGs. A PKG is a representation of all relevant common-sense knowledge and personal data for a user and can support the development of innovative applications such as a digitalized personalized coach. It empowers stakeholders to make more effective decisions. This book explores in a structured manner the global advanced research around PKGs to support the development of innovative digitalized personalized applications such as personal banking, personalized book-keeping, daily health-related activities monitoring and goal management tracking. The authors present methodologies, tools and applications including innovative topics tailored for PKGs such as named entity recognition and linking, construction approaches, modelling of personalization and context-awareness, evaluation approaches, relation extraction techniques, query answering in user specific knowledge graphs, knowledge representation and reasoning (KRR), visualization tools, integration tools and techniques, and fact summarization. The book provides systematic coverage of this complex topic for researchers, scientists and engineers in both industry and academia working in data science, ICTs, knowledge engineering, semantic web, reasoning, information retrieval, and machine and deep learning with a focus on knowledge graphs. Advanced students with an interest in the field will also find this to be a useful resource.
Language: English
Published by Cambridge University Press, Cambridge, 2026
ISBN 10: 1009513745 ISBN 13: 9781009513746
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condition: new. Hardcover. Knowledge-infused learning directly confronts the opacity of current 'black-box' AI models by combining data-driven machine learning techniques with the structured insights of symbolic AI. This guidebook introduces the pioneering techniques of neurosymbolic AI, which blends statistical models with symbolic knowledge to make AI safer and user-explainable. This is critical in high-stakes AI applications in healthcare, law, finance, and crisis management. The book brings readers up to speed on advancements in statistical AI, including transformer models such as BERT and GPT, and provides a comprehensive overview of weakly supervised, distantly supervised, and unsupervised learning methods alongside their knowledge-enhanced variants. Other topics include active learning, zero-shot learning, and model fusion. Beyond theory, the book presents practical considerations and applications of neurosymbolic AI in conversational systems, mental health, crisis management systems, and social and behavioral sciences, making it a pragmatic reference for AI system designers in academia and industry. This practical guidebook introduces an emerging field that confronts the opacity of current 'black-box' AI models. Knowledge-infused learning combines machine learning and symbolic AI to make AI safer and more explainable, which is vital for applications in human-critical contexts such as healthcare, law, and finance. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.