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Machine Learning Engineer Professional-Machine-Learning-Engineer Passing Score

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Question 20

You have successfully deployed to production a large and complex TensorFlow model trained on tabular data. You want to predict the lifetime value (LTV) field for each subscription stored in the BigQuery table named subscription. subscriptionPurchase in the project named my-fortune500-company-project.

You have organized all your training code, from preprocessing data from the BigQuery table up to deploying the validated model to the Vertex AI endpoint, into a TensorFlow Extended (TFX) pipeline. You want to prevent prediction drift, i.e., a situation when a feature data distribution in production changes significantly over time. What should you do?

Options:

A.

Implement continuous retraining of the model daily using Vertex AI Pipelines.

B.

Add a model monitoring job where 10% of incoming predictions are sampled 24 hours.

C.

Add a model monitoring job where 90% of incoming predictions are sampled 24 hours.

D.

Add a model monitoring job where 10% of incoming predictions are sampled every hour.

Question 21

Your team trained and tested a DNN regression model with good results. Six months after deployment, the model is performing poorly due to a change in the distribution of the input data. How should you address the input differences in production?

Options:

A.

Create alerts to monitor for skew, and retrain the model.

B.

Perform feature selection on the model, and retrain the model with fewer features

C.

Retrain the model, and select an L2 regularization parameter with a hyperparameter tuning service

D.

Perform feature selection on the model, and retrain the model on a monthly basis with fewer features

Question 22

You have recently developed a custom model for image classification by using a neural network. You need to automatically identify the values for learning rate, number of layers, and kernel size. To do this, you plan to run multiple jobs in parallel to identify the parameters that optimize performance. You want to minimize custom code development and infrastructure management. What should you do?

Options:

A.

Create a Vertex Al pipeline that runs different model training jobs in parallel.

B.

Train an AutoML image classification model.

C.

Create a custom training job that uses the Vertex Al Vizier SDK for parameter optimization.

D.

Create a Vertex Al hyperparameter tuning job.

Question 23

You work for a gaming company that manages a popular online multiplayer game where teams with 6 players play against each other in 5-minute battles. There are many new players every day. You need to build a model that automatically assigns available players to teams in real time. User research indicates that the game is more enjoyable when battles have players with similar skill levels. Which business metrics should you track to measure your model’s performance? (Choose One Correct Answer)

Options:

A.

Average time players wait before being assigned to a team

B.

Precision and recall of assigning players to teams based on their predicted versus actual ability

C.

User engagement as measured by the number of battles played daily per user

D.

Rate of return as measured by additional revenue generated minus the cost of developing a new model

Page: 5 / 20
Exam Name: Google Professional Machine Learning Engineer
Last Update: Nov 1, 2024
Questions: 270
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