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."Sinopsis" puede pertenecer a otra edición de este libro.
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."Sobre este título" puede pertenecer a otra edición de este libro.
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Taschenbuch. Condición: 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. 512 pp. Englisch. Nº de ref. del artículo: 9783031436031
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Taschenbuch. Condición: Neu. Machine Learning for Econometrics and Related Topics | Vladik Kreinovich (u. a.) | Taschenbuch | Studies in Systems, Decision and Control | ix | Englisch | 2025 | Springer | EAN 9783031436031 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 133788917
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 512 pp. Englisch. Nº de ref. del artículo: 9783031436031
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783031436031
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