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‘Machine Learning for Knowledge Discovery with R’ contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes most recent supervised and unsupervised machine learning methodologies
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This lucid and coherent introduction to supervised machine learning presents core concepts in a concise, logical and easy-to-follow way for readers... Læs mere
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Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that integrates literature... Læs mere
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This book equips readers with the knowledge to data analytics, machine learning and deep learning techniques for applications defined under the umbrella of Industry 4.0.
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Support Vector Machines are now established as one of the standard tools for machine learning and data mining. Students... Læs mere
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Optimization techniques are at the core of data science. An understanding of the basic techniques and their fundamental properties provides important grounding for... Læs mere
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This modern and self-contained book offers a clear and accessible introduction to the important topic of machine... Læs mere
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This comprehensive text on the theory and techniques of graph neural networks takes students, practitioners, and researchers from the basics to the state of the art. It... Læs mere
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This book provides a practical introduction to compressive imaging (with examples and code), an overview of core topics, and a comprehensive, rigorous... Læs mere
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This book introduces machine learning in finance and illustrates how to integrate computational tools with numerical finance with real world applications.