Practice Professional-Machine-Learning-Engineer Exam Online

Question 1

You are an ML engineer at an ecommerce company and have been tasked with building a model that predicts how much inventory the logistics team should order each month. Which approach should you take?

A : Use a clustering algorithm to group popular items together. Give the list to the logistics team so they can increase inventory of the popular items.

B : Use a regression model to predict how much additional inventory should be purchased each month. Give the results to the logistics team at the beginning of the month so they can increase inventory by the amount predicted by the model.

C : Use a time series forecasting model to predict each item's monthly sales. Give the results to the logistics team so they can base inventory on the amount predicted by the model.

D : Use a classification model to classify inventory levels as UNDER_STOCKED, OVER_STOCKED, and CORRECTLY_STOCKEGive the report to the logistics team each month so they can fine-tune inventory levels.

Answer: B

Question 2

You work at a leading healthcare firm developing state-of-the-art algorithms for various use cases You have unstructured textual data with custom labels You need to extract and classify various medical phrases with these labels What should you do?

A : Use the Healthcare Natural Language API to extract medical entities.

B : Use a BERT-based model to fine-tune a medical entity extraction model.

C : Use AutoML Entity Extraction to train a medical entity extraction model.

D : Use TensorFlow to build a custom medical entity extraction model.

Answer: B

Question 3

You work for a magazine distributor and need to build a model that predicts which customers will renew their subscriptions for the upcoming year. Using your company’s historical data as your training set, you created a TensorFlow model and deployed it to Vertex AI. You need to determine which customer attribute has the most predictive power for each prediction served by the model. What should you do?

A : Stream prediction results to BigQuery. Use BigQuery’s CORR(X1, X2) function to calculate the Pearson correlation coefficient between each feature and the target variable.

B : Use the What-If tool in Google Cloud to determine how your model will perform when individual features are excluded. Rank the feature importance in order of those that caused the most significant performance drop when removed from the model.

C : Use Vertex AI Workbench user-managed notebooks to perform a Lasso regression analysis on your model, which will eliminate features that do not provide a strong signal.

D : Use Vertex Explainable AI. Submit each prediction request with the explain' keyword to retrieve feature attributions using the sampled Shapley method.

Answer: B

Question 4

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 service

account.

3. Provision a Vertex Al Workbench user-managed notebook instance that uses the default Compute

Engine 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 users

account.

Answer: C

Question 5

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 : Train 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 : Develop 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 : Develop 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 : Hire 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

Name:	Professional Machine Learning Engineer
Exam Code:	Professional-Machine-Learning-Engineer
Certification:	Google Cloud Certified
Vendor:	Google
Total Questions:	298
Last Updated:	Apr 23, 2024

Google Professional-Machine-Learning-Engineer