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A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to real world problems. This book tackles this... Læs mere
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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.
Bemærk: Kan ikke leveres før jul.
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.
Bemærk: Kan ikke leveres før jul.
Bemærk: Kan ikke leveres før jul.
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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Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the... 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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Edited by two of the leading experts in the field, this book provides a comprehensive reference book on feature engineering. The book provides a description of problems and applications for feature engineering, as well as its techniques, principles, issues, and challenges.
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This new volume, Empowering Artificial intelligence Through Machine Learning: New Advances and Applications, discusses various new... Læs mere
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This book explores the frontiers and challenges of applying Artificial Intelligence (AI) techniques to Sensor Networks. It covers how sensor... 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.