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[null,"1.","Record Nr.",null,"UNINA9911066010503321"]
[null,null,"Autore",null,"Pedrycz Witold"]
[null,null,"Titolo",null,"Advances in Intelligent Data and Information Processing : Proceedings of the International Conference on Intelligent Data and Information Processing (IDIP2025), Volume 2 / / edited by Witold Pedrycz, John Wang, Kuo-Kun Tseng, Xilong Qu"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026"]
[null,null,"ISBN",null,"3-032-16702-7"]
[null,null,"Edizione",null,"[1st ed. 2026.]"]
[null,null,"Descrizione fisica",null,"1 online resource (418 pages)"]
[null,null,"Collana",null,"Lecture Notes in Networks and Systems, , 2367-3389 ; ; 1808"]
[null,null,"Disciplina",null,"620.00285"]
[null,null,"Soggetti",null,"Engineering - Data processing"]
[{"$nulls":4},"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Data Engineering"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- Application of Fused Neural Network Model in English Sentiment Analysis -- Research on Prediction of Housing Security Demand Based on Big Data and its Impact on Policy Making -- Deep Learning Model Optimization for Natural Language Processing -- Early Warning Model Construction of Enterprise Financial Crisis Based on Random Forest Algorithm, etc."]
[null,null,null,"Sommario/riassunto","This book integrates practical engineering insights with cutting-edge AI/ML methodologies to address real-world intelligent data processing challenges, prioritizing actionable solutions over theoretical abstraction. By bridging algorithmic foundations with industry-specific use cases, it equips readers to translate technical concepts into deployable systems efficiently. Unlike traditional texts that silo theory and practice, this approach embeds hands-on implementation frameworks, including data preprocessing pipelines, model optimization techniques, and scalability strategies, directly within contextualized problem-solving scenarios. Covering core topics from edge AI deployment to large-scale data analytics, it spans both foundational principles and emerging trends like federated learning and real-time processing. Tailored for IT professionals, computer "]
[{"$nulls":4},"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."]