A company wants to fine-tune a Gemini model to generate product descriptions from product attributes. They have a large dataset of product attributes and descriptions stored in BigQuery. They want to use BigQuery to prepare the data for fine-tuning. The data includes some rows with missing descriptions. What should they do to prepare the data?

Export the entire table to JSONL, including rows with missing descriptions, and let the fine-tuning process handle them

Export the data to CSV format and use it directly for fine-tuning

Use BigQuery ML to train a model to impute the missing descriptions before exporting

Filter out rows with missing descriptions, then export the remaining data to JSONL format in Cloud Storage

Google CloudProfessional Machine Learning Engineer

Domain 1Objective 1

Developing ML Models Using BigQuery ML or AutoML on Gemini Enterprise Agent Platform PROFESSIONAL-MACHINE-LEARNING-ENGINEER Practice Questions (Page 6)

Part of the Architecting low-code AI solutions domain, which accounts for ~13% of the PROFESSIONAL-MACHINE-LEARNING-ENGINEER exam.

26questions here

6free pages

10concepts

~13%of the exam

10 Concepts in This Objective

Selecting BigQuery ML model types
Building classification models in BigQuery ML
Building regression models in BigQuery ML
Building forecasting models in BigQuery ML
Building clustering models in BigQuery ML
Performing feature engineering in BigQuery ML
Performing feature selection in BigQuery ML
Generating predictions with BigQuery ML
Training models with Agent Platform AutoML
Fine-tuning Gemini models using BigQuery

Questions 26–26

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A company wants to fine-tune a Gemini model to generate product descriptions from product attributes. They have a large dataset of product attributes and descriptions stored in BigQuery. They want to use BigQuery to prepare the data for fine-tuning. The data includes some rows with missing descriptions. What should they do to prepare the data?
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Developing ML Models Using BigQuery ML or AutoML on Gemini Enterprise Agent Platform PROFESSIONAL-MACHINE-LEARNING-ENGINEER Practice Questions (Page 6)

Questions 26–26

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