Advances in Intelligent Data and Information Processing: Proceedings of the International Conference on Intelligent Data and Information Processing ... 1808 (Lecture Notes in Networks and Systems) - Tapa blanda

 
9783032167019: Advances in Intelligent Data and Information Processing: Proceedings of the International Conference on Intelligent Data and Information Processing ... 1808 (Lecture Notes in Networks and Systems)
Tapa blanda
ISBN 10: 3032167019 ISBN 13: 9783032167019
Editorial: Springer, 2026

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2026
Idioma
Inglés
ISBN 10 
3032167019
ISBN 13 
9783032167019
Encuadernación
Tapa blanda
Número de páginas
316
Editor
Pedrycz Witold, Wang John, Tseng Kuo-Kun, Qu Xilong
Contacto del fabricante
Springer Nature Customer Service Center GmbH
ProductSafety@springernature.com

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