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ISBN 10: 3837664791 ISBN 13: 9783837664799
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Paperback. Condition: new. Paperback. Food is more than just nutrition. Its preparation, presentation and consumption is a multifold communicative practice which includes the meal's design and its whole field of experience. How is food represented in cookbooks, product packaging or in paintings? How is dining semantically charged? How is the sensuality of eating treated in different cultural contexts? In order to acknowledge the material and media-related aspects of eating as a cultural praxis, experts from media studies, art history, literary studies, philosophy, experimental psychology, ethnology, food studies, cultural studies and design studies share their special approaches. Food is so much more than just nutrition an interdisciplinary study of eating as a cultural practice. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Condition: New. Food is more than just nutrition. Its preparation, presentation and consumption is a multifold communicative practice which includes the meal's design and its whole field of experience. How is food represented in cookbooks, product packaging or in paintings? How is dining semantically charged? How is the sensuality of eating treated in different cultural contexts? In order to acknowledge the material and media-related aspects of eating as a cultural praxis, experts from media studies, art history, literary studies, philosophy, experimental psychology, anthropology, food studies, cultural studies and design studies share their specific approaches.
Language: English
Published by Springer Verlag, Singapore, Singapore, 2022
ISBN 10: 9811951721 ISBN 13: 9789811951725
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First Edition
Paperback. Condition: new. Paperback. This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The case studies presented in this book can be run on a regular desktop or notebook computer. No high-performance computing facilities are required. The idea for the book originated in a study conducted by Bartz & Bartz GmbH for the Federal Statistical Office of Germany (Destatis). Building on that study, the book is addressed to practitioners in industry as well as researchers, teachers and students in academia. The content focuses on the hyperparameter tuning of ML and DL algorithms, and is divided into two main parts: theory (Part I) and application (Part II).Essential topics covered include: a survey of important model parameters; four parameter tuning studies and one extensive global parameter tuning study; statistical analysis of the performance of ML and DL methods based on severity; and a new, consensus-ranking-based way to aggregate and analyze results from multiple algorithms. The book presents analyses of more than 30 hyperparameters from six relevant ML and DL methods, and provides source code so that users can reproduce the results. Accordingly, it serves as a handbook and textbook alike. This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Language: English
Published by transcript publishing, 2024
ISBN 10: 3837664791 ISBN 13: 9783837664799
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Language: English
Published by transcript publishing, 2024
ISBN 10: 3837664791 ISBN 13: 9783837664799
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Language: English
Published by Springer Verlag, Singapore, Singapore, 2023
ISBN 10: 9811951691 ISBN 13: 9789811951695
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
First Edition
Hardcover. Condition: new. Hardcover. This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The case studies presented in this book can be run on a regular desktop or notebook computer. No high-performance computing facilities are required. The idea for the book originated in a study conducted by Bartz & Bartz GmbH for the Federal Statistical Office of Germany (Destatis). Building on that study, the book is addressed to practitioners in industry as well as researchers, teachers and students in academia. The content focuses on the hyperparameter tuning of ML and DL algorithms, and is divided into two main parts: theory (Part I) and application (Part II).Essential topics covered include: a survey of important model parameters; four parameter tuning studies and one extensive global parameter tuning study; statistical analysis of the performance of ML and DL methods based on severity; and a new, consensus-ranking-based way to aggregate and analyze results from multiple algorithms. The book presents analyses of more than 30 hyperparameters from six relevant ML and DL methods, and provides source code so that users can reproduce the results. Accordingly, it serves as a handbook and textbook alike. This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Language: English
Published by transcript publishing, 2024
ISBN 10: 3837664791 ISBN 13: 9783837664799
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Published by transcript publishing, 2024
ISBN 10: 3837664791 ISBN 13: 9783837664799
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Published by transcript publishing, 2024
ISBN 10: 3837664791 ISBN 13: 9783837664799
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Published by transcript publishing, 2024
ISBN 10: 3837664791 ISBN 13: 9783837664799
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