Which SQL statement correctly uses ML.PREDICT to generate predictions from a BigQuery ML model named `sales_model` on data in table `new_sales_data`?

SELECT * FROM ML.PREDICT(MODEL sales_model, TABLE new_sales_data);

SELECT * FROM ML.EVALUATE(MODEL sales_model, TABLE new_sales_data);

SELECT * FROM ML.FEATURE_INFO(MODEL sales_model);

SELECT * FROM ML.TRAINING_INFO(MODEL sales_model);

A company wants to fine-tune a Gemini model using their own customer support conversation data. The data is currently in a BigQuery table with columns `prompt` and `response`. They want to use BigQuery to prepare the data and then invoke the fine-tuning process. Which approach should they use?

Export the BigQuery table to a JSONL file in Cloud Storage and use it for fine-tuning in Vertex AI

Use BigQuery ML to train a Gemini model directly on the table

Use the BigQuery ML.CREATE_MODEL function with model_type='GEMINI'

Load the BigQuery data into a Vertex AI dataset and then launch a custom training job

In Agent Platform AutoML, what is the purpose of configuring training options before launching a training job?

To evaluate the model after training

To specify the model type and training parameters

To deploy the model to production

After preparing the training data in BigQuery, how is the fine-tuning process for a Gemini model typically invoked?

By using a separate service or API call

By running a BigQuery ML training job

By exporting data to a CSV file

By creating a new BigQuery dataset

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 5)

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 21–25

21foundation · easy
Which SQL statement correctly uses ML.PREDICT to generate predictions from a BigQuery ML model named `sales_model` on data in table `new_sales_data`?
Select an answer first
22application · medium
A company wants to fine-tune a Gemini model using their own customer support conversation data. The data is currently in a BigQuery table with columns `prompt` and `response`. They want to use BigQuery to prepare the data and then invoke the fine-tuning process. Which approach should they use?
Select an answer first
23foundation · easy
A marketing team wants to segment customers into distinct groups based on purchasing behavior without predefined labels. Which BigQuery ML model type should be used?
Select an answer first
24foundation · easy
In Agent Platform AutoML, what is the purpose of configuring training options before launching a training job?
Select an answer first
25foundation · easy
After preparing the training data in BigQuery, how is the fine-tuning process for a Gemini model typically invoked?
Select an answer first

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