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Topics include neural network learning, knowledge acquisition and learning, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.

Machine learning --- Machine learning.

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This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

Machine learning

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Computational Intelligence and Intelligent Technologies are very important tools in building intelligent systems with various degree of autonomous behaviour These groups of tools support such features as ability to learn and adaptability of the intelligent systems in various types of environments and situations The current and future Information Society is expecting to be implemented with the framework of the Ambient Intelligence (AmI) approach into technologies and everyday life.

Machine learning

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Machine learning

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Machine learning