Google Professional Machine Learning Engineer
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You are an ML engineer at an ecommerce company and have been tasked with building a predictive model to assist the logistics team in determining the monthly inventory levels for various items. The goal is to ensure that inventory levels are optimized, avoiding both understocking and overstocking situations. Which approach should you take?
A
Use a clustering algorithm to group popular items together. Give the list to the logistics team so they can increase inventory of the popular items.
B
Use a regression model to predict how much additional inventory should be purchased each month. Give the results to the logistics team at the beginning of the month so they can increase inventory by the amount predicted by the model.
C
Use a time series forecasting model to predict each item's monthly sales. Give the results to the logistics team so they can base inventory on the amount predicted by the model.
D
Use a classification model to classify inventory levels as UNDER_STOCKED, OVER_STOCKED, and CORRECTLY_STOCKED. Give the report to the logistics team each month so they can fine-tune inventory levels._