Explainable AI: Foundations, Methodologies and Applications (Intelligent Systems Reference Library, 232)

ISBN 10: 3031128060 ISBN 13: 9783031128066

Edit� par Springer, 2022

Neuf(s) Couverture rigide

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This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.

The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.

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Titre : Explainable AI: Foundations, Methodologies ...
�diteur : Springer
Date d'�dition : 2022
Reliure : Couverture rigide
Etat : New

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Explainable AI: Foundations, Methodologies and Applications

Edit� par Springer, Berlin|Springer International Publishing|Springer, 2022

ISBN 10 : 3031128060 ISBN 13 : 9783031128066

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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/. N� de r�f. du vendeur 668447348

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Explainable AI: Foundations, Methodologies and Applications

Mayuri Mehta (u. a.)

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ISBN 10 : 3031128060 ISBN 13 : 9783031128066

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Explainable AI: Foundations, Methodologies and Applications (Intelligent Systems Reference Library, 232)

Edit� par Springer, 2022

ISBN 10 : 3031128060 ISBN 13 : 9783031128066

Neuf Couverture rigide

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Explainable AI: Foundations, Methodologies and Applications

Mayuri Mehta; Vasile Palade; Indranath Chatterjee

Edit� par Springer International Publishing, 2022

ISBN 10 : 3031128060 ISBN 13 : 9783031128066

Neuf Couverture souple

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Etat : New. Idioma/Language: Ingl�s. This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas. The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations. *** Nota: Los env�os a Espa�a peninsular, Baleares y Canarias se realizan a trav�s de mensajer�a urgente. No aceptamos pedidos con destino a Ceuta y Melilla. N� de r�f. du vendeur 22736755

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Explainable AI: Foundations, Methodologies and Applications

Mayuri Mehta

Edit� par Springer International Publishing, 2022

ISBN 10 : 3031128060 ISBN 13 : 9783031128066

Neuf Couverture rigide

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations. N� de r�f. du vendeur 9783031128066

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Explainable AI: Foundations, Methodologies and Applications

Mayuri Mehta

Edit� par Springer International Publishing, Springer International Publishing Okt 2022, 2022

ISBN 10 : 3031128060 ISBN 13 : 9783031128066

Neuf Couverture rigide

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

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Buch. Etat : Neu. Neuware -This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 280 pp. Englisch. N� de r�f. du vendeur 9783031128066

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Explainable AI: Foundations, Methodologies and Applications

Mayuri Mehta

Edit� par Springer International Publishing Okt 2022, 2022

ISBN 10 : 3031128060 ISBN 13 : 9783031128066

Neuf Couverture rigide

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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations. 280 pp. Englisch. N� de r�f. du vendeur 9783031128066

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