Google Cloud Professional Machine Learning Engineer — Question 86

You are an ML engineer at an ecommerce company and have been tasked with building a model that predicts how much inventory the logistics team should order each month. Which approach should you take?

Answer options

• 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_STOCKEGive the report to the logistics team each month so they can fine-tune inventory levels.

Correct answer: C

Explanation

The correct approach is to use a time series forecasting model to predict each item's monthly sales, as it takes into account historical sales data and trends. This method allows the logistics team to make informed inventory decisions based on accurate sales predictions. Clustering and classification models do not directly predict quantities needed, while regression models may not effectively capture the seasonal and temporal nature of sales data.