Distributed Deep Learning Explainable (8 results)

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    • Language: English

      Published by Springer, 2025

      3031946367 / 9783031946363

      • Hardcover

      Seller: Books Puddle, New York, NY, U.S.A.Books Puddle

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    • Language: English

      Published by Birkhäuser, 2025

      3031946367 / 9783031946363

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      Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a comprehensive resource that delves into the integration of advanced artificial intelligence techniques within the context of modern industrial practices. It systematically explores how distributed deep learning methodologies can be effectively combined with explainable AI to enhance transparency in Industry 4.0 applications. In recent years, neural networks and other deep learning models have produced remarkable outcomes in a variety of fields, including image recognition, natural language processing, and decision-making. Concerns have been raised regarding the transparency and interpretability of these models as a result of their increasing intricacy. The demand for methodologies and approaches associated with explainable artificial intelligence (XAI) has consequently increased. The primary aim of XAI is to enhance the transparency and comprehensibility of deep learning model decision-making processes for stakeholders, irrespective of their technical expertise.

    • Language: English

      Published by Springer, 2025

      3031946367 / 9783031946363

      • Hardcover
      • Print on Demand

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    • Language: English

      Published by Springer Verlag GmbH, 2025

      3031946367 / 9783031946363

      • Hardcover
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      Seller: moluna, Greven, Germanymoluna

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    • Language: English

      Published by Springer, Berlin, Springer Nature Switzerland, Springer, 2025

      3031946367 / 9783031946363

      • Hardcover
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      Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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      Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a comprehensive resource that delves into the integration of advanced artificial intelligence techniques within the context of modern industrial practices. It systematically explores how distributed deep learning methodologies can be effectively combined with explainable AI to enhance transparency in Industry 4.0 applications. In recent years, neural networks and other deep learning models have produced remarkable outcomes in a variety of fields, including image recognition, natural language processing, and decision-making. Concerns have been raised regarding the transparency and interpretability of these models as a result of their increasing intricacy. The demand for methodologies and approaches associated with explainable artificial intelligence (XAI) has consequently increased. The primary aim of XAI is to enhance the transparency and comprehensibility of deep learning model decision-making processes for stakeholders, irrespective of their technical expertise. 424 pp. Englisch.

    • Language: English

      Published by Springer, Palgrave Macmillan Sep 2025, 2025

      3031946367 / 9783031946363

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      Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

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      Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is a comprehensive resource that delves into the integration of advanced artificial intelligence techniques within the context of modern industrial practices. It systematically explores how distributed deep learning methodologies can be effectively combined with explainable AI to enhance transparency in Industry 4.0 applications. In recent years, neural networks and other deep learning models have produced remarkable outcomes in a variety of fields, including image recognition, natural language processing, and decision-making. Concerns have been raised regarding the transparency and interpretability of these models as a result of their increasing intricacy. The demand for methodologies and approaches associated with explainable artificial intelligence (XAI) has consequently increased. The primary aim of XAI is to enhance the transparency and comprehensibility of deep learning model decision-making processes for stakeholders, irrespective of their technical expertise.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 432 pp. Englisch.

    • Language: English

      Published by Springer, 2025

      3031946367 / 9783031946363

      • Hardcover
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      Seller: Majestic Books, Hounslow, United KingdomMajestic Books

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    • Language: English

      Published by Springer, 2025

      3031946367 / 9783031946363

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      Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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