This book brings together innovative research at the intersection of data science, machine learning, and finance. Covering a wide spectrum of topics―including explainable AI, financial distress prediction, stock market forecasting, investment strategies, audit analytics, and economic modeling―it showcases both theoretical developments and applied case studies from around the world.
With chapters spanning predictive modeling, sentiment analysis, capital structure, IT governance, and Bayesian approaches to productivity, the book offers a multidisciplinary perspective on how data-driven tools are reshaping modern finance and accounting.
This book presents a timely resource for academics, practitioners, and graduate students seeking to understand and apply data science in financial and accounting contexts.
"Sinopsis" puede pertenecer a otra edición de este libro.
This book brings together innovative research at the intersection of data science, machine learning, and finance. Covering a wide spectrum of topics--including explainable AI, financial distress prediction, stock market forecasting, investment strategies, audit analytics, and economic modeling--it showcases both theoretical developments and applied case studies from around the world.
With chapters spanning predictive modeling, sentiment analysis, capital structure, IT governance, and Bayesian approaches to productivity, the book offers a multidisciplinary perspective on how data-driven tools are reshaping modern finance and accounting.
This book presents a timely resource for academics, practitioners, and graduate students seeking to understand and apply data science in financial and accounting contexts.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: moluna, Greven, Alemania
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book brings together innovative research at the intersection of data science, machine learning, and finance. Covering a wide spectrum of topics including explainable AI, financial distress prediction, stock market forecasting, investment strategies, audit analytics, and economic modeling it showcases both theoretical developments and applied case studies from around the world.With chapters spanning predictive modeling, sentiment analysis, capital structure, IT governance, and Bayesian approaches to productivity, the book offers a multidisciplinary perspective on how data-driven tools are reshaping modern finance and accounting.This book presents a timely resource for academics, practitioners, and graduate students seeking to understand and apply data science in financial and accounting contexts. 378 pp. Englisch. Nº de ref. del artículo: 9783032061782
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Hardback. Condición: New. This book brings together innovative research at the intersection of data science, machine learning, and finance. Covering a wide spectrum of topics-including explainable AI, financial distress prediction, stock market forecasting, investment strategies, audit analytics, and economic modeling-it showcases both theoretical developments and applied case studies from around the world.With chapters spanning predictive modeling, sentiment analysis, capital structure, IT governance, and Bayesian approaches to productivity, the book offers a multidisciplinary perspective on how data-driven tools are reshaping modern finance and accounting.This book presents a timely resource for academics, practitioners, and graduate students seeking to understand and apply data science in financial and accounting contexts. Nº de ref. del artículo: LU-9783032061782
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book brings together innovative research at the intersection of data science, machine learning, and finance. Covering a wide spectrum of topicsincluding explainable AI, financial distress prediction, stock market forecasting, investment strategies, audit analytics, and economic modelingit showcases both theoretical developments and applied case studies from around the world.With chapters spanning predictive modeling, sentiment analysis, capital structure, IT governance, and Bayesian approaches to productivity, the book offers a multidisciplinary perspective on how data-driven tools are reshaping modern finance and accounting.This book presents a timely resource for academics, practitioners, and graduate students seeking to understand and apply data science in financial and accounting contexts.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 388 pp. Englisch. Nº de ref. del artículo: 9783032061782
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Hardcover. Condición: new. Hardcover. This book brings together innovative research at the intersection of data science, machine learning, and finance. Covering a wide spectrum of topicsincluding explainable AI, financial distress prediction, stock market forecasting, investment strategies, audit analytics, and economic modelingit showcases both theoretical developments and applied case studies from around the world.With chapters spanning predictive modeling, sentiment analysis, capital structure, IT governance, and Bayesian approaches to productivity, the book offers a multidisciplinary perspective on how data-driven tools are reshaping modern finance and accounting.This book presents a timely resource for academics, practitioners, and graduate students seeking to understand and apply data science in financial and accounting contexts. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9783032061782
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