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Data Science for Economics and Finance (Paperback)
Language: English
Published by Springer Nature Switzerland AG, Cham, 2021
ISBN 10: 3030668932 ISBN 13: 9783030668938
First Edition
Paperback. Condition: new. Paperback. This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models.The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Data Science for Economics and Finance: Methodologies and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Data Science for Economics and Finance : Methodologies and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Data Science for Economics and Finance : Methodologies and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Data Science for Economics and Finance: Methodologies and Applications
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Data Science for Economics and Finance : Methodologies and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Data Science for Economics and Finance : Methodologies and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Data Science for Economics and Finance: Methodologies and Applications
Language: English
Published by Springer-Nature New York Inc, 2021
ISBN 10: 3030668932 ISBN 13: 9783030668938
Paperback. Condition: Brand New. 372 pages. 9.25x6.10x0.88 inches. In Stock.
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Hardcover. Condition: Brand New. 369 pages. 9.25x6.10x0.94 inches. In Stock.
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Data Science for Economics and Finance (Paperback)
Language: English
Published by Springer Nature Switzerland AG, Cham, 2021
ISBN 10: 3030668932 ISBN 13: 9783030668938
First Edition
Paperback. Condition: new. Paperback. This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models.The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Data Science for Economics and Finance : Methodologies and Applications
Language: English
Published by Springer International Publishing, 2021
ISBN 10: 3030668932 ISBN 13: 9783030668938
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models.The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis.This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
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Global Sensitivity Analysis: The Primer
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Taschenbuch. Condition: Neu. Data Science for Economics and Finance | Methodologies and Applications | Sergio Consoli (u. a.) | Taschenbuch | xiv | Englisch | 2021 | Springer | EAN 9783030668938 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Data Science for Economics and Finance : Methodologies and Applications
Language: English
Published by Springer International Publishing, 2021
ISBN 10: 3030668908 ISBN 13: 9783030668907
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models.The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis.This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
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Condition: New. pp. x + 292 Illus.
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Condition: New. pp. x + 292.
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Sensitivity Analysis of Scientific Models
Published by Wiley-Interscience, 2008
ISBN 10: 0470059974 ISBN 13: 9780470059975
Hardcover. Condition: Brand New. illustrated edition. 304 pages. 9.25x6.25x1.00 inches. In Stock.
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Condition: new. Questo è un articolo print on demand.
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Data Science for Economics and Finance: Methodologies and Applications
Language: English
Published by Springer-Nature New York Inc, 2021
ISBN 10: 3030668932 ISBN 13: 9783030668938
Paperback. Condition: Brand New. 372 pages. 9.25x6.10x0.88 inches. In Stock. This item is printed on demand.
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Data Science for Economics and Finance
Language: English
Published by Springer International Publishing Jun 2021, 2021
ISBN 10: 3030668932 ISBN 13: 9783030668938
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models.The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis.This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications. 372 pp. Englisch.
