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.
Edited by:
Witold Pedrycz, John Wang, Kuo-Kun Tseng, Xilong Qu Imprint: Springer Nature Switzerland AG Country of Publication: Switzerland Dimensions:
Height: 235mm,
Width: 155mm,
ISBN:9783032167019 ISBN 10: 3032167019 Series:Lecture Notes in Networks and Systems Pages: 304 Publication Date:23 February 2026 Audience:
College/higher education
,
Professional and scholarly
,
Further / Higher Education
,
Undergraduate
Format:Paperback Publisher's Status: Active
.- Application of Fused Neural Network Model in English Sentiment Analysis.- Research on Prediction of Housing Security Demand Based on Big Data and its Impact on Policy Making.- Deep Learning Model Optimization for Natural Language Processing.- Early Warning Model Construction of Enterprise Financial Crisis Based on Random Forest Algorithm, etc.