Enterprise-Scale Machine Learning for Demand Forecasting
M. Harshvardhan,
Cara Curtland,
Adam Ghozeil and
Chuanren Liu
Foresight: The International Journal of Applied Forecasting, 2025, issue 79, 20-25
Abstract:
This article charts HP's voyage from simplistic statistical methods to an integrated, enterprise-grade forecasting pipeline powered by LightGBM, robust machine learning operations (MLOps), and augmented by human-in-the-loop design. Copyright International Institute of Forecasters, 2025
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://forecasters.org/foresight/bookstore/
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:for:ijafaa:y:2025:i:79:p:20-25
Access Statistics for this article
More articles in Foresight: The International Journal of Applied Forecasting from International Institute of Forecasters Contact information at EDIRC.
Bibliographic data for series maintained by Michael Gilliland ().