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Business forecasting : the emerging role of artificial intelligence and machine learning /

"Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term This book...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Gilliland, Michael (Editor ), Tashman, Len, 1942- (Editor ), Sglavo, Udo, 1968- (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, New Jersey : John Wiley & Sons, Inc., [2021]
Colección:Wiley and SAS business series.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 0 0 |a Business forecasting :  |b the emerging role of artificial intelligence and machine learning /  |c edited by Michael Gilliland, Len Tashman, Udo Sglavo. 
264 1 |a Hoboken, New Jersey :  |b John Wiley & Sons, Inc.,  |c [2021] 
300 |a 1 online resource (xvii, 414 pages) :  |b illustrations (some color). 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Wiley and SAS business series 
504 |a Includes bibliographical references and index. 
520 |a "Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term This book provides ideas from the most important and influential authors in the field of forecasting on an array of topics that are highly relevant. It provides multiple perspectives on relevant issues like monitoring forecast performance, forecasting process, communication and accountability for the forecast, the use of big data in forecasting, and the role of AI/ML in enhancing traditional time series forecasting methods. Note: Content is mostly material previously published in "practitioner" journals (Foresight and Journal of Business Forecasting), with a few articles from the academic International Journal of Forecasting. Some articles report on academic research, or include case studies, but most are thoughtful discussion of important business forecasting topics, such as the role of the sales force in forecasting, or the value of judgmental overrides to a statistical forecast, or how to determine what forecast error is "avoidable." Articles were chosen for their importance, influence, informativeness, and for being provocative -- leading the reader to new considerations and ideas"--  |c Provided by publisher. 
588 |a Description based on online resource; title from digital title page (viewed on May 26, 2021). 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Business forecasting. 
650 0 |a Artificial intelligence. 
650 0 |a Machine learning. 
650 2 |a Artificial Intelligence 
650 2 |a Machine Learning 
650 6 |a Prévision commerciale. 
650 6 |a Intelligence artificielle. 
650 6 |a Apprentissage automatique. 
650 7 |a artificial intelligence.  |2 aat 
650 7 |a Artificial intelligence  |2 fast 
650 7 |a Business forecasting  |2 fast 
650 7 |a Machine learning  |2 fast 
700 1 |a Gilliland, Michael,  |e editor. 
700 1 |a Tashman, Len,  |d 1942-  |e editor. 
700 1 |a Sglavo, Udo,  |d 1968-  |e editor. 
710 2 |a John Wiley & Sons,  |e publisher. 
776 0 8 |i Print version:  |t Business forecasting  |d Hoboken, New Jersey : Wiley, 2021.  |z 9781119782476  |w (DLC) 2021002141 
830 0 |a Wiley and SAS business series. 
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