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Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Databases

• Plný název: Advances in Intelligent Data and Information Processing
• Podnázev: Proceedings of the International Conference on Intelligent Data and Information Processing (IDIP2025). Volume 1
• Autor: Witold Pedrycz, John Wang, Kuo-Kun Tseng, Xilong Qu
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 342
• EAN: 9783032167040
• ID: 50211162
• Nakladatelství: Springer, Berlin
• Hmotnost: 522 g
• Rozměry: 235 × 155 mm
• Datum vydání: 15. February 2026

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