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This book provides a comprehensive exploration of generalization in deep learning, focusing on both theoretical foundations and practical strategies. It delves deeply into how machine learning models, particularly deep neural networks, achieve robust performance on unseen data.
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This book shows how AI tools and techniques, such as artificial neural networks, machine learning algorithms,... Læs mere
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This book offers a groundbreaking exploration of how Artificial Intelligence is revolutionizing... Læs mere
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This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes.
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This book comprehensively explores the latest technological advancements in healthcare, with a particular focus on the application of... Læs mere
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This book comprehensively explores the latest technological advancements in healthcare, with a particular focus on the application of... Læs mere
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This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial... Læs mere
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The text comprehensively discusses computational models including artificial neural networks, agent-based... Læs mere
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Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications.
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This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. It presents... Læs mere
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This reference text aims to systematically collect quality research spanning AI, ML and Deep Learning (DL)... Læs mere
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This book presents the advances in AI techniques under the umbrella of Intelligent Computing. The book provides theoretical, algorithmic, simulation, and implementation-based recent research advancements related to the Intelligent Computing.