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Herausgeber: 
  • Diego Reforgiato Recupero
  • Michaela Saisana
  • Sergio Consoli
  • Data Science for Economics and Finance: Methodologies and Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Juni 2021  
    Genre:  EDV / Informatik 
     
    bigdata / Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften / Data Mining / Data Warehousing / DataAnalytics / datamining / decisionsupportsystems / Informationsrückgewinnung, Information Retrieval
    ISBN:  9783030668938 
    EAN-Code: 
    9783030668938 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 21 mm 
    Gewicht:  563 gr 
    Seiten:  372 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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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