Machine Learning for Econometrics and Related Topics (Hardcover)
Language: English
Published by Springer International Publishing AG, Cham, 2024
- Hardcover
- New

Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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US$ 375.27
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Add to basketItem description from seller
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.…
Seller Inventory # 9783031436000
- Title
- Machine Learning for Econometrics and Related Topics (Hardcover)
- Author
- Vladik Kreinovich
- Publisher
- Springer International Publishing AG, Cham
- Publication year
- 2024
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3031436008
- ISBN 13
- 9783031436000
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."Synopsis" may belong to another edition of this title.
From the Back Cover
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."About the title" may belong to another edition of this title.
Grand Eagle Retail
Bensenville, IL, U.S.A.
AbeBooks seller since October 12, 2005
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