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This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time.
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The book covers several of the major data analysis techniques used to analyze data from high-throughput molecular biology and genomics experiments. It also explains the major concepts behind most of the popular techniques and examines some of the simpler techniques in detail.
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This book illustrates the range of tasks and design choices in current music generation research, applying machine learning techniques and highlighting recurring... Læs mere
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The main purpose of the text is to present the student with just enough of the R language, machine learning algorithms, and... Læs mere
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This book discusses various aspects of agent-based modeling and simulation using FLAME (Flexible Large-scale Agent-Based Modeling Environment).... Læs mere
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This book introduces reinforcement learning, and provides novel ideas and use cases to demonstrate the benefits of using reinforcement learning for Cyber Physical Systems. Two important case studies on applying reinforcement learning to cybersecurity problems are included.
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Based on the author’s experience teaching data science for more than 10 years, Mathematics and R Programming for Machine Learning reveals how machine learning algorithms do their magic and explains how logic can be implemented in code.
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This book shows how machine learning can be applied to address real-world problems in the fourth industrial revolution and provides the required knowledge and... Læs mere
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Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the process of analyzing data to... Læs mere
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The book encompasses the state-of-the-art visual quality assessment (VQA) and learning based visual quality assessment (LB-VQA) by providing a comprehensive overview of the existing relevant methods.
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Bemærk: Kan ikke leveres før jul.