GitHub - MaharanaSaroj/StoreSales-Time-Series-Forecasting: The goal of this analysis is to predict the sales for the thousands of product families sold at Favorita stores located in Ecuador. Predictions aren’t just for meteorologists. Governments forecast economic growth. Scientists attempt to predict the future population. And businesses forecast product demand—a common task of professional data scientists. Forecasts are especially relevant to brick-and-mortar grocery stores, which must dance delicately with how much inventory to buy. Predict a little over, and grocers are stuck with overstocked, perishable goods. Guess a little under, and popular items quickly sell out, leading to lost revenue and upset customers. More accurate forecasting, thanks to machine learning, could help ensure retailers please customers by having just enough of the right products at the right time.

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The goal of this analysis is to predict the sales for the thousands of product families sold at Favorita stores located in Ecuador. Predictions aren’t just for meteorologists. Governments forecast economic growth. Scientists attempt to predict the future population. And businesses forecast product demand—a common task of professional data scientis…

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