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{ "item_title" : "Advances in Intelligent Data and Information Processing", "item_author" : [" Witold Pedrycz", "John Wang", "Kuo-Kun Tseng "], "item_description" : "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. ", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/03/216/701/3032167019_b.jpg", "price_data" : { "retail_price" : "219.99", "online_price" : "219.99", "our_price" : "219.99", "club_price" : "219.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Advances in Intelligent Data and Information Processing|Witold Pedrycz

Advances in Intelligent Data and Information Processing : Proceedings of the International Conference on Intelligent Data and Information Processing (I

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Overview

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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Details

  • ISBN-13: 9783032167019
  • ISBN-10: 3032167019
  • Publisher: Springer
  • Publish Date: February 2026
  • Dimensions: 9.21 x 6.14 x 0.67 inches
  • Shipping Weight: 0.98 pounds
  • Page Count: 304

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