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Exam Code: Professional-Machine-Learning-Engineer
Exam Title: Google Professional Machine Learning Engineer
Vendor: Google
Exam Questions: 60
Last Updated: September 28th,2024

Question 1

You have written unit tests for a Kubeflow Pipeline that require custom libraries. You want to automate the execution of unit tests with each new push to your development branch in Cloud Source Repositories. What should you do?

A. Write a script that sequentially performs the push to your development branch and executes the unit tests on Cloud Run
B. Using Cloud Build, set an automated trigger to execute the unit tests when changes are pushed to your development branch.
C. Set up a Cloud Logging sink to a Pub/Sub topic that captures interactions with Cloud Source Repositories Configure a Pub/Sub trigger for Cloud Run, and execute the unit tests on Cloud Run.
D. Set up a Cloud Logging sink to a Pub/Sub topic that captures interactions with Cloud Source Repositorie
E. Execute the unit tests using a Cloud Function that is triggered when messages are sent to the Pub/Sub topic

Correct Answer:B

Question 2

Your team is working on an NLP research project to predict political affiliation of authors based on articles they have written. You have a large training dataset that is structured like this:
Professional-Machine-Learning-Engineer dumps exhibit
A)

B)

C)

D)

A. Option A
B. Option B
C. Option C
D. Option D

Correct Answer:D

Question 3

You need to build classification workflows over several structured datasets currently stored in BigQuery.
Because you will be performing the classification several times, you want to complete the following steps without writing code: exploratory data analysis, feature selection, model building, training, and hyperparameter tuning and serving. What should you do?

A. Configure AutoML Tables to perform the classification task
B. Run a BigQuery ML task to perform logistic regression for the classification
C. Use Al Platform Notebooks to run the classification model with pandas library
D. Use Al Platform to run the classification model job configured for hyperparameter tuning

Correct Answer:C

Question 4

Your team is building an application for a global bank that will be used by millions of customers. You built a forecasting model that predicts customers1 account balances 3 days in the future. Your team will use the results in a new feature that will notify users when their account balance is likely to drop below $25. How should you serve your predictions?

A. 1. Create a Pub/Sub topic for each user* 2 Deploy a Cloud Function that sends a notification when your model predicts that a user's account balance will drop below the $25 threshold.
B. 1. Create a Pub/Sub topic for each user* 2. Deploy an application on the App Engine standard environment that sends a notification when your model predicts thata user's account balance will drop below the $25 threshold
C. 1. Build a notification system on Firebase* 2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when the average of all account balance predictions drops below the $25 threshold
D. 1 Build a notification system on Firebase* 2. Register each user with a user ID on the Firebase Cloud Messaging server, which sends a notification when your model predicts that a user's account balance will drop below the $25 threshold

Correct Answer:B

Question 5

You are building an ML model to detect anomalies in real-time sensor data. You will use Pub/Sub to handle incoming requests. You want to store the results for analytics and visualization. How should you configure the pipeline?
Professional-Machine-Learning-Engineer dumps exhibit

A. 1 = Dataflow, 2 - Al Platform, 3 = BigQuery
B. 1 = DataProc, 2 = AutoML, 3 = Cloud Bigtable
C. 1 = BigQuery, 2 = AutoML, 3 = Cloud Functions
D. 1 = BigQuery, 2 = Al Platform, 3 = Cloud Storage

Correct Answer:C