Free Google Professional-Machine-Learning-Engineer Exam Questions

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

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Total 289 Questions | Updated On: Feb 21, 2026

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Question 1

You have deployed multiple versions of an image classification model on AI Platform. You want to monitor the performance of the model versions over time. How should you perform this comparison?

A : mpare the loss performance for each model on a held-out dataset.

B : mpare the loss performance for each model on the validation data.

C : mpare the receiver operating characteristic (ROC) curve for each model using the What-If Tool.

D : mpare the mean average precision across the models using the Continuous Evaluation feature.

Answer: B

Question 2

You work for a bank You have been asked to develop an ML model that will support loan application decisions. You need to determine which Vertex Al services to include in the workflow You want to track the model's training parameters and the metrics per training epoch. You plan to compare the performance of each version of the model to determine the best model based on your chosen metrics. Which Vertex Al services should you use?

A : Vertex ML Metadata Vertex Al Feature Store, and Vertex Al Vizier

B : Vertex Al Pipelines. Vertex Al Experiments, and Vertex Al Vizier

C : Vertex ML Metadata Vertex Al Experiments, and Vertex Al TensorBoard

D : Vertex Al Pipelines. Vertex Al Feature Store, and Vertex Al TensorBoard

Answer: D

Question 3

You have developed a BigQuery ML model that predicts customer churn and deployed the model to Vertex Al Endpoints. You want to automate the retraining of your model by using minimal additional code when model feature values change. You also want to minimize the number of times that your model is retrained to reduce training costs. What should you do?

A : 1. Enable request-response logging on Vertex Al Endpoints.2 Schedule a TensorFlow Data Validation job to monitor prediction drift3. Execute model retraining if there is significant distance between the distributions

B : 1. Enable request-response logging on Vertex Al Endpoints2. Schedule a TensorFlow Data Validation job to monitor training/serving skew3. Execute model retraining if there is significant distance between the distributions

C : 1 Create a Vertex Al Model Monitoring job configured to monitor prediction drift.2. Configure alert monitoring to publish a message to a Pub/Sub queue when a monitonng alert isdetected.3. Use a Cloud Function to monitor the Pub/Sub queue, and trigger retraining in BigQuery

D : 1. Create a Vertex Al Model Monitoring job configured to monitor training/serving skew2. Configure alert monitoring to publish a message to a Pub/Sub queue when a monitoring alert isdetected3. Use a Cloud Function to monitor the Pub/Sub queue, and trigger retraining in BigQuery.

Answer: C

Question 4

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

Question 5

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

Page: 1 / 58

Total 289 Questions | Updated On: Feb 21, 2026

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