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Aggiungi al carrelloCondizione: Hervorragend. Zustand: Hervorragend | Seiten: 348 | Sprache: Englisch | Produktart: Bücher | This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance.It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies.The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworks.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Data Analytics for Management, Banking and Finance | Theories and Application | Foued Saâdaoui (u. a.) | Taschenbuch | xiv | Englisch | 2024 | Springer | EAN 9783031365720 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Da: Books Puddle, New York, NY, U.S.A.
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Editore: Springer Nature Switzerland, Springer Nature Switzerland Sep 2024, 2024
ISBN 10: 3031365720 ISBN 13: 9783031365720
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance.It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies.The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworksSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 348 pp. Englisch.
Editore: Springer Nature Switzerland, Springer International Publishing Sep 2023, 2023
ISBN 10: 3031365690 ISBN 13: 9783031365690
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware -This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance.It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies.The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworksSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 348 pp. Englisch.
Editore: Springer Nature Switzerland, Springer International Publishing, 2024
ISBN 10: 3031365720 ISBN 13: 9783031365720
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 192,59
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance.It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies.The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworks.
Editore: Springer Nature Switzerland, Springer Nature Switzerland, 2023
ISBN 10: 3031365690 ISBN 13: 9783031365690
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 192,59
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance.It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies.The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworks.
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Editore: Springer, Berlin|Springer Nature Switzerland|Springer, 2023
ISBN 10: 3031365690 ISBN 13: 9783031365690
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 162,51
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business ana.
Editore: Springer Nature Switzerland, Springer Nature Switzerland Sep 2023, 2023
ISBN 10: 3031365690 ISBN 13: 9783031365690
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 192,59
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance.It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies.The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworks 348 pp. Englisch.
Editore: Springer Nature Switzerland, Springer International Publishing Sep 2024, 2024
ISBN 10: 3031365720 ISBN 13: 9783031365720
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 192,59
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance.It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies.The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworks 348 pp. Englisch.
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EUR 169,20
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Aggiungi al carrelloBuch. Condizione: Neu. Data Analytics for Management, Banking and Finance | Theories and Application | Foued Saâdaoui (u. a.) | Buch | xiv | Englisch | 2023 | Springer | EAN 9783031365690 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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EUR 261,89
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Da: Biblios, Frankfurt am main, HESSE, Germania
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