Advances in Intelligent Data and Information Processing: Proceedings of the International Conference on Intelligent Data and Information Processing (IDIP2025), Volume 1: 1809 - Brossura

Brossura

ISBN 10: 3032167043 ISBN 13: 9783032167040

Casa editrice: Springer, 2026

Riassunto

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.

Su questo libro

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Springer
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 3032167043
• ISBN 13: 9783032167040
• Rilegatura: Copertina flessibile
• Numero di pagine: 344
• Redattore: Pedrycz Witold, Wang John, Tseng Kuo-Kun, Qu Xilong
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3,69115 Heidelberg, Germany; Heidelberg; 69115; Germania