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Business Forecasting

The Emerging Role of Artificial Intelligence and Machine Learning, SAS Institute Inc
ISBN/EAN: 9781119782476
Umbreit-Nr.: 984105

Sprache: Englisch
Umfang: 432 S.
Format in cm:
Einband: gebundenes Buch

Erschienen am 24.06.2021
Auflage: 1/2021
€ 57,90
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  • Zusatztext
    • Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: * Discussions on deep learning in forecasting, including current trends and challenges * Explorations of neural network-based forecasting strategies * A treatment of the future of artificial intelligence in business forecasting * Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 "opinion/editorial" Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.

  • Kurztext
    • Prepare for the ongoing and future impact of AI and machine learning on business forecasting with dozens of insightful resources While modern business forecasting is only 60 years old, its impact has been enormous and wide-ranging. From keeping supermarket shelves stocked to informing the decisions of business executives across the world, business forecasting is the foundation for much of the global economy. Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning offers readers a collection of over 60 of the most impactful, insightful, and provocative articles and commentaries on the growing impact of AI and machine learning on the practice of business forecasting. Ranging in subjects from the role of neural networks in forecasting strategies to big data in supply-chain forecasting, judgmental forecast model selection, and the use of forecast error metrics, the book dives deep into topics of central importance to modern forecasting and machine learning. Ideal for financial controllers and other executives engaging with forecasts for decision making in companies of all sizes and across a wide range of industries, Business Forecasting will also earn a place in the libraries of business analysts, forecast managers and directors, and demand planners who hope to stay on the cutting-edge of what business forecasting has to offer.

  • Autorenportrait
    • MICHAEL GILLILAND is Marketing Manager for SAS forecasting software and Associate Editor of Foresight: The International Journal of Applied Forecasting. He is author of The Business Forecasting Deal. LEN TASHMAN is the founding editor of Foresight: The International Journal of Applied Forecasting. He is emeritus professor of business administration at the University of Vermont and Director of the Center for Business Forecasting. UDO SGLAVO is Vice President of Analytics R&D at SAS and holds several patents in the area of advanced analytics. His writings have appeared in Analytics magazine and the book Big Data and Business Analytics.
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