Machine Learning for Econometrics and Related Topics - Couverture rigide

9783031436000: Machine Learning for Econometrics and Related Topics

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ISBN 10 : 3031436008 ISBN 13 : 9783031436000

Editeur : Springer International Publishing AG, 2024

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In the last decades, machine learning techniques – especially techniques of deep learning – led to numerous successes in many application areas, including economics.

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�diteur: Springer International Publishing AG
Date d'�dition: 2024
Langue: anglais
ISBN 10: 3031436008
ISBN 13: 9783031436000
Reliure: Reli�
Nombre de pages: 508
�diteur: Kreinovich Vladik, Sriboonchitta Songsak, Yamaka Woraphon
Coordonn�es du fabricant: ProductSafety@springernature.com
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Machine Learning for Econometrics and Related Topics

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ISBN 10 : 3031436008 ISBN 13 : 9783031436000

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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Describes the use of more traditional econometric techniquesFocuses on the use of machine learning in economicsIncludes applications of economics in agriculture, health, manufacturing, trade, and transportationIn the last decades. N� de r�f. du vendeur 1027290426

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Machine Learning for Econometrics and Related Topics (Hardcover)

Vladik Kreinovich

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Hardcover. Etat : new. Hardcover. In the last decades, machine learning techniques especially techniques of deep learning led to numerous successes in many application areas, including economics. The use of machine learning in economics is the main focus of this book; however, the book also describes the use of more traditional econometric techniques. Applications include practically all major sectors of economics: agriculture, health (including the impact of Covid-19), manufacturing, trade, transportation, etc. Several papers analyze the effect of age, education, and gender on economy and, more generally, issues of fairness and discrimination.We hope that this volume will:help practitioners to become better knowledgeable of the state-of-the-art econometric techniques, especially techniques of machine learning,and help researchers to further develop these important research directions. We want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments. In the last decades, machine learning techniques especially techniques of deep learning led to numerous successes in many application areas, including economics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9783031436000

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Machine Learning for Econometrics and Related Topics

Vladik Kreinovich

Edit� par Springer, Berlin, Springer Nature Switzerland, Springer Nov 2023, 2023

ISBN 10 : 3031436008 ISBN 13 : 9783031436000

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the last decades, machine learning techniques - especially techniques of deep learning - led to numerous successes in many application areas, including economics. The use of machine learning in economics is the main focus of this book; however, the book also describes the use of more traditional econometric techniques. Applications include practically all major sectors of economics: agriculture, health (including the impact of Covid-19), manufacturing, trade, transportation, etc. Several papers analyze the effect of age, education, and gender on economy - and, more generally, issues of fairness and discrimination.We hope that this volume will:help practitioners to become better knowledgeable of the state-of-the-art econometric techniques, especially techniques of machine learning,and help researchers to further develop these important research directions. We want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments. 499 pp. Englisch. N� de r�f. du vendeur 9783031436000

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Machine Learning for Econometrics and Related Topics

Vladik Kreinovich (u. a.)

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Machine Learning for Econometrics and Related Topics

Vladik Kreinovich

Edit� par Springer Nature Switzerland, Springer International Publishing Jun 2024, 2024

ISBN 10 : 3031436008 ISBN 13 : 9783031436000

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Buch. Etat : Neu. Neuware -In the last decades, machine learning techniques � especially techniques of deep learning � led to numerous successes in many application areas, including economics. The use of machine learning in economics is the main focus of this book; however, the book also describes the use of more traditional econometric techniques. Applications include practically all major sectors of economics: agriculture, health (including the impact of Covid-19), manufacturing, trade, transportation, etc. Several papers analyze the effect of age, education, and gender on economy � and, more generally, issues of fairness and discrimination.We hope that this volume will:help practitioners to become better knowledgeable of the state-of-the-art econometric techniques, especially techniques of machine learningand help researchers to further develop these important research directions. We want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 512 pp. Englisch. N� de r�f. du vendeur 9783031436000

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Machine Learning for Econometrics and Related Topics

Vladik Kreinovich

Edit� par Springer Nature Switzerland, 2024

ISBN 10 : 3031436008 ISBN 13 : 9783031436000

Neuf Couverture rigide

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - In the last decades, machine learning techniques - especially techniques of deep learning - led to numerous successes in many application areas, including economics. The use of machine learning in economics is the main focus of this book; however, the book also describes the use of more traditional econometric techniques. Applications include practically all major sectors of economics: agriculture, health (including the impact of Covid-19), manufacturing, trade, transportation, etc. Several papers analyze the effect of age, education, and gender on economy - and, more generally, issues of fairness and discrimination.We hope that this volume will:help practitioners to become better knowledgeable of the state-of-the-art econometric techniques, especially techniques of machine learning,and help researchers to further develop these important research directions. We want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments. N� de r�f. du vendeur 9783031436000

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