Topic 1 Question 294
You work for a company that sells corporate electronic products to thousands of businesses worldwide. Your company stores historical customer data in BigQuery. You need to build a model that predicts customer lifetime value over the next three years. You want to use the simplest approach to build the model. What should you do?
Create a Vertex AI Workbench notebook. Use IPython magic to run the CREATE MODEL statement to create an ARIMA model.
Access BigQuery Studio in the Google Cloud console. Run the CREATE MODEL statement in the SQL editor to create an AutoML regression model.
Create a Vertex AI Workbench notebook. Use IPython magic to run the CREATE MODEL statement to create an AutoML regression model.
Access BigQuery Studio in the Google Cloud console. Run the CREATE MODEL statement in the SQL editor to create an ARIMA model.
ユーザの投票
コメント(2)
- 正解だと思う選択肢: B
A and C (Vertex AI Workbench): While Vertex AI Workbench is a powerful platform for ML development, it requires setting up a notebook environment and writing Python code, which adds complexity compared to using BigQuery ML directly. D (ARIMA model): ARIMA models are specifically designed for time series forecasting. While they might be applicable in some CLTV scenarios, AutoML Regression provides a more general and potentially more accurate solution for predicting CLTV based on various customer features.
👍 5AB_C2024/11/27 - 正解だと思う選択肢: B
Exclude A and C because the question specifies "the simplest approach". BigQuery Studio is more immediate than Vertex AI Workbench
Both ARIMA and AutoML works as modeling technique for customer lifetime value. The question specifies "the simplest approach", hence B AutoML is chosen over D ARIMA.
👍 1MarcoPellegrino2025/01/14
シャッフルモード