Google Professional Machine Learning Engineer Question 84
Select 4Google Cloud PlatformYour team is tasked with building a demand forecasting model for a retail chain to predict daily sales for each store over the next month. You decide to use AutoML in Google Cloud to create the forecasting model. Which of the following steps should you take to ensure the model is trained and deployed successfully?
- A
Prepare the data by formatting it into a tabular format with a time column and target column, and upload it to BigQuery or Cloud Storage.
- B
Enable the 'Time Series Forecasting' option in AutoML Tables and configure the forecast horizon and context window.
- C
Train the model without specifying a prediction type, as AutoML will automatically detect it.
- D
Evaluate the model's performance using metrics like RMSE and MAPE to ensure it meets the business requirements.
- E
Deploy the trained model to an endpoint in Vertex AI to serve predictions for the retail chain.
Show answer and explanation
Correct answers: A, B, D, E
Explanation
To create a forecasting model with AutoML, proper preparation and configuration are critical. Preparing the data in a tabular format, enabling the correct forecasting options, and evaluating model performance ensure a successful training process. Finally, deploying the model to an endpoint allows it to deliver predictions in real-world scenarios. However, specifying the prediction type is mandatory, as AutoML cannot automatically determine this.
- A. Correct.
Correct: AutoML requires input data to be in a structured tabular format, including a time column for time-series forecasting. Uploading the data to BigQuery or Cloud Storage ensures compatibility with AutoML.
- B. Correct.
Correct: For forecasting tasks, you must explicitly enable the 'Time Series Forecasting' option in AutoML Tables and configure parameters like the forecast horizon (how far into the future to predict) and context window (historical data used for making predictions).
- C. Incorrect.
Incorrect: You must specify the prediction type when using AutoML, such as regression for forecasting. AutoML does not automatically detect the prediction type.
- D. Correct.
Correct: Evaluating the model with appropriate metrics like RMSE (Root Mean Squared Error) and MAPE (Mean Absolute Percentage Error) is essential to ensure the model aligns with business needs and goals.
- E. Correct.
Correct: Deploying the trained model to an endpoint in Vertex AI allows it to serve predictions in a production environment for the retail chain.