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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1705
DC FieldValueLanguage
dc.contributor.authorKien Minh Huyen_US
dc.date.accessioned2023-10-03T04:21:28Z-
dc.date.available2023-10-03T04:21:28Z-
dc.date.issued2023-
dc.identifier.urihttps://epub.vgu.edu.vn/handle/dlibvgu/1705-
dc.description.abstractThe article analyzes grocery sales – time series forecasting by using Kaggle which is a dataset applying the Machine Learning method. The study focuses on Favorita Corporation, a prominent Ecuadorian grocer, provided the statistics. Implementing Python, the process will create a framework that more precisely forecasts sales per unit for thousands of products supplied at various Favorita stores. The framework includes an accessible dataset for training containing dates, store and product details, promotions, and sales by unit. By merging and combining the datasets, the model brings out extensive connectivity between them which builds up a time series forecasting for retail sales in Ecuador country.en_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectstores salesen_US
dc.subjectTime series forecastingen_US
dc.subjectKaggleen_US
dc.subjectPythonen_US
dc.titleStore sales – time series forecasting in Ecuador using kaggleen_US
dc.typeThesisen_US
item.grantfulltextrestricted-
item.languageiso639-1other-
item.fulltextWith Fulltext-
Appears in Collections:Finance & Accounting (FA)
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