Data Science Finance Accounting (15 results)

Condition: New.

Hardback. Condition: New.

Condition: New.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Hardcover. Condition: Brand New. 386 pages. 9.26x6.11x9.21 inches. In Stock.

Book. Condition: New.

paperback. Condition: New. Paperback.Pub Date:2023-09 Pages:348 Language:Chinese Publisher:Northeast University of Finance and Economics Press This book provides a solid and concise foundation in audit theory and uses R code to actually perform audit tasks and decisions. The author applies the latest machine learning models to identify subtle patterns in audit evidence that may escape traditional audit methods. providing readers with a list of basic algorithms that can be easily extended and customized to help auditors.

Hardcover. Condition: 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 multiple locations in the US or from the UK, depending on stock availability.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Buch. Condition: 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.

Buch. Condition: 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.

Hardcover. Condition: 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.

Condition: New. Print on Demand.

Hardcover. Condition: 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 Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condition: New. PRINT ON DEMAND.