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Condition: New. 1st ed. 2019 edition NO-PA16APR2015-KAP.
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Language: English
Published by Springer-Verlag New York Inc, 2019
ISBN 10: 9811335818 ISBN 13: 9789811335815
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Advances in Data Science, ICIIT 2018, held in Chennai, India, in December 2018.The 11 full papers along with 4 short papers presented were carefully reviewed and selected from 74 submissions.The papers are organized in topical sections ondata science foundations, data management and processing technologies, data analytics and its applications.
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. 1st ed. 2018 edition NO-PA16APR2015-KAP.
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. Softcover reprint of the original 1st ed. 2018 edition NO-PA16APR2015-KAP.
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Language: English
Published by Engineering Science Reference, 2019
ISBN 10: 1799812901 ISBN 13: 9781799812906
Seller: Books From California, Simi Valley, CA, U.S.A.
hardcover. Condition: Very Good.
Taschenbuch. Condition: Neu. Advances in Intelligent Data and Information Processing | Proceedings of the International Conference on Intelligent Data and Information Processing (IDIP2025), Volume 2 | Witold Pedrycz (u. a.) | Taschenbuch | Lecture Notes in Networks and Systems | ix | Englisch | 2026 | Springer | EAN 9783032167019 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Condition: New. pp. 1188 1st ed. 2020 edition NO-PA16APR2015-KAP.
Taschenbuch. Condition: Neu. Advances in Intelligent Data and Information Processing | Proceedings of the International Conference on Intelligent Data and Information Processing (IDIP2025), Volume 1 | Witold Pedrycz (u. a.) | Taschenbuch | Lecture Notes in Networks and Systems | ix | Englisch | 2026 | Springer | EAN 9783032167040 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Condition: New. 1st ed. 2023 edition NO-PA16APR2015-KAP.
Condition: Gut. Zustand: Gut | Seiten: 1209 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book integrates practical engineering insights with cutting-edge AI/ML methodologies to address real-world intelligent data processing challenges, prioritizing actionable solutions over theoretical abstraction. By bridging algorithmic foundations with industry-specific use cases, it equips readers to translate technical concepts into deployable systems efficiently.Unlike traditional texts that silo theory and practice, this approach embeds hands-on implementation frameworks, including data preprocessing pipelines, model optimization techniques, and scalability strategies, directly within contextualized problem-solving scenarios. Covering core topics from edge AI deployment to large-scale data analytics, it spans both foundational principles and emerging trends like federated learning and real-time processing.Tailored for IT professionals, computer science practitioners, and engineering researchers, it also serves as a valuable resource for graduate students specializing in data science or intelligent systems. Ideal for upskilling, project reference, or curriculum supplementation, it empowers readers to tackle complex data-intensive tasks with confidence in academic, corporate, or R&D settings.
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book integrates practical engineering insights with cutting-edge AI/ML methodologies to address real-world intelligent data processing challenges, prioritizing actionable solutions over theoretical abstraction. By bridging algorithmic foundations with industry-specific use cases, it equips readers to translate technical concepts into deployable systems efficiently.Unlike traditional texts that silo theory and practice, this approach embeds hands-on implementation frameworks, including data preprocessing pipelines, model optimization techniques, and scalability strategies, directly within contextualized problem-solving scenarios. Covering core topics from edge AI deployment to large-scale data analytics, it spans both foundational principles and emerging trends like federated learning and real-time processing.Tailored for IT professionals, computer science practitioners, and engineering researchers, it also serves as a valuable resource for graduate students specializing in data science or intelligent systems. Ideal for upskilling, project reference, or curriculum supplementation, it empowers readers to tackle complex data-intensive tasks with confidence in academic, corporate, or R&D settings.
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