PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #306
PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #306: Real Exam Question with Answer & Explanation
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Question
You work at a retail company, and are tasked with developing an ML model to predict product sales. Your company's historical sales data is stored in BigQuery and includes features such as date, store location, product category, and promotion details. You need to choose the most effective combination of a BigQuery ML model and feature engineering to maximize prediction accuracy. What should you do?
Options
- AUse a linear regression model. Perform one-hot encoding on categorical features, and create
- BUse a boosted tree model. Perform label encoding on categorical features, and transform the date
- CUse an autoencoder model. Perform label encoding on categorical features, and normalize the
- DUse a matrix factorization model. Perform one-hot encoding on categorical features, and create
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