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OverviewIn 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. Full Product DetailsAuthor: Vladik Kreinovich , Songsak Sriboonchitta , Woraphon YamakaPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 2024 ed. Volume: 508 ISBN: 9783031436000ISBN 10: 3031436008 Pages: 499 Publication Date: 02 June 2024 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |