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: Mar 24, 2026

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Question 1

You built a deep learning-based image classification model by using on-premises data. You want to use Vertex Al to deploy the model to production Due to security concerns you cannot move your data to the cloud. You are aware that the input data distribution might change over time You need to detect model performance changes in production. What should you do?

A : Use Vertex Explainable Al for model explainability Configure feature-based explanations.

B : Use Vertex Explainable Al for model explainability Configure example-based explanations.

C : Create a Vertex Al Model Monitoring job. Enable training-serving skew detection for your model.

D : Create a Vertex Al Model Monitoring job. Enable feature attribution skew and dnft detection for your model.

Answer: D

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 are collaborating on a model prototype with your team. You need to create a Vertex Al Workbench environment for the members of your team and also limit access to other employees in your project. What should you do?

A : 1. Create a new service account and grant it the Notebook Viewer role.2 Grant the Service Account User role to each team member on the service account.3 Grant the Vertex Al User role to each team member.4. Provision a Vertex Al Workbench user-managed notebook instance that uses the new service account.

B : 1. Grant the Vertex Al User role to the default Compute Engine service account.2. Grant the Service Account User role to each team member on the default Compute Engine serviceaccount.3. Provision a Vertex Al Workbench user-managed notebook instance that uses the default ComputeEngine service account.

C : 1 Create a new service account and grant it the Vertex Al User role.2 Grant the Service Account User role to each team member on the service account.3. Grant the Notebook Viewer role to each team member.4 Provision a Vertex Al Workbench user-managed notebook instance that uses the new service account.

D : 1 Grant the Vertex Al User role to the primary team member.2. Grant the Notebook Viewer role to the other team members.3. Provision a Vertex Al Workbench user-managed notebook instance that uses the primary usersaccount.

Answer: C

Question 4

You need to train a natural language model to perform text classification on product descriptions that contain millions of examples and 100,000 unique words. You want to preprocess the words individually so that they can be fed into a recurrent neural network. What should you do?

A : eate a hot-encoding of words, and feed the encodings into your model.

B : entify word embeddings from a pre-trained model, and use the embeddings in your model.

C : rt the words by frequency of occurrence, and use the frequencies as the encodings in your model.

D : ign a numerical value to each word from 1 to 100,000 and feed the values as inputs in your model

Answer: B

Question 5

You are building a linear regression model on BigQuery ML to predict a customer’s likelihood of purchasing your company’s products. Your model uses a city name variable as a key predictive component. In order to train and serve the model, your data must be organized in columns. You want to prepare your data using the least amount of coding while maintaining the predictable variables. What should you do?

A : TensorFlow to create a categorical variable with a vocabulary list. Create the vocabulary file, and upload it as part of your model to BigQuery ML.

B : eate a new view with BigQuery that does not include a column with city information

C : Cloud Data Fusion to assign each city to a region labeled as 1, 2, 3, 4, or 5, and then use that number to represent the city in the model.

D : Dataprep to transform the state column using a one-hot encoding method, and make each city a column with binary values.

Answer: B

Page: 1 / 58

Total 289 Questions | Updated On: Mar 24, 2026

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