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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: Books Puddle, New York, NY, Estados Unidos de America
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Idioma: Inglés
Publicado por Springer-Nature New York Inc, 2021
ISBN 10: 3030668932 ISBN 13: 9783030668938
Librería: Revaluation Books, Exeter, Reino Unido
EUR 73,98
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Añadir al carritoPaperback. Condición: Brand New. 372 pages. 9.25x6.10x0.88 inches. In Stock.
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Añadir al carritoHardcover. Condición: Brand New. 369 pages. 9.25x6.10x0.94 inches. In Stock.
Idioma: Inglés
Publicado por Springer International Publishing, 2021
ISBN 10: 3030668932 ISBN 13: 9783030668938
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 42,79
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Añadir al carritoTaschenbuch. Condición: 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.
EUR 96,85
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Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: 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.
Idioma: Inglés
Publicado por Springer International Publishing, 2021
ISBN 10: 3030668908 ISBN 13: 9783030668907
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 53,49
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Añadir al carritoBuch. Condición: 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.
EUR 121,18
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Añadir al carritoCondición: New. pp. x + 292 Illus.
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Añadir al carritoCondición: New. pp. x + 292.
EUR 131,46
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Añadir al carritoBuch. Condición: Neu. Neuware - Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard.Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications.The book:\* Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials.\* Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls.\* Features numerous exercises and solved problems to help illustrate the applications.\* Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds.Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.
Publicado por Wiley-Interscience, 2008
ISBN 10: 0470059974 ISBN 13: 9780470059975
Librería: Revaluation Books, Exeter, Reino Unido
EUR 168,26
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Añadir al carritoHardcover. Condición: Brand New. illustrated edition. 304 pages. 9.25x6.25x1.00 inches. In Stock.
Librería: Basi6 International, Irving, TX, Estados Unidos de America
EUR 51,15
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Añadir al carritoCondición: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 46,22
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Librería: Basi6 International, Irving, TX, Estados Unidos de America
EUR 58,21
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Añadir al carritoCondición: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Idioma: Inglés
Publicado por Springer International Publishing Jun 2021, 2021
ISBN 10: 3030668932 ISBN 13: 9783030668938
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 42,79
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: 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.