Free Google Professional-Machine-Learning-Engineer Exam Questions

Become Google Certified with updated Professional-Machine-Learning-Engineer exam questions and correct answers

Page: 1 / 58

Total 289 Questions | Updated On: Jan 12, 2026

Add To Cart

Question 1

You recently designed and built a custom neural network that uses critical dependencies specific to your organization’s framework. You need to train the model using a managed training service on Google Cloud. However, the ML framework and related dependencies are not supported by AI Platform Training. Also, both your model and your data are too large to fit in memory on a single machine. Your ML framework of choice uses the scheduler, workers, and servers distribution structure. What should you do?

A : a built-in model available on AI Platform Training.

B : ild your custom container to run jobs on AI Platform Training.

C : ild your custom containers to run distributed training jobs on AI Platform Training.

D : configure your code to a ML framework with dependencies that are supported by AI Platform Training.

Answer: D

Question 2

You work for an advertising company and want to understand the effectiveness of your company's latest advertising campaign. You have streamed 500 MB of campaign data into BigQuery. You want to query the table, and then manipulate the results of that query with a pandas dataframe in an AI Platform notebook.

What should you do?

A : AI Platform Notebooks' BigQuery cell magic to query the data, and ingest the results as a pandas dataframe.

B : port your table as a CSV file from BigQuery to Google Drive, and use the Google Drive API to ingest the file into your notebook instance.

C : wnload your table from BigQuery as a local CSV file, and upload it to your AI Platform notebook instance. Use pandas.read_csv to ingest he file as a pandas dataframe.

D : om a bash cell in your AI Platform notebook, use the bq extract command to export the table as a CSV file to Cloud Storage, and then use gsutil cp to copy the data into the notebook. Use pandas.read_csv to ingest the file as a pandas dataframe.

Answer: C

Question 3

You work on a team in a data center that is responsible for server maintenance. Your management team wants you to build a predictive maintenance solution that uses monitoring data to detect potential server failures. Incident data has not been labeled yet. What should you do first?

A : ain a time-series model to predict the machines’ performance values. Configure an alert if a machine’s actual performance values significantly differ from the predicted performance values.

B : velop a simple heuristic (e.g., based on z-score) to label the machines’ historical performance data. Use this heuristic to monitor server performance in real time.

C : velop a simple heuristic (e.g., based on z-score) to label the machines’ historical performance data. Train a model to predict anomalies based on this labeled dataset.

D : re a team of qualified analysts to review and label the machines’ historical performance data. Train a model based on this manually labeled dataset.

Answer: D

Question 4

During batch training of a neural network, you notice that there is an oscillation in the loss. How should you adjust your model to ensure that it converges?

A : crease the size of the training batch.

B : crease the learning rate hyperparameter.

C : crease the learning rate hyperparameter.

Answer: C

Question 5

You are developing an ML model to predict house prices. While preparing the data, you discover that an important predictor variable, distance from the closest school, is often missing and does not have high variance. Every instance (row) in your data is important. How should you handle the missing data?

A : lete the rows that have missing values.

B : ply feature crossing with another column that does not have missing values.

C : edict the missing values using linear regression.

D : place the missing values with zeros.

Answer: C

Page: 1 / 58

Total 289 Questions | Updated On: Jan 12, 2026

Add To Cart