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Professional-Machine-Learning-Engineer Google Exam Lab Questions

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Question 44

You are developing a model to help your company create more targeted online advertising campaigns. You need to create a dataset that you will use to train the model. You want to avoid creating or reinforcing unfair bias in the model. What should you do?

Choose 2 answers

Options:

A.

Include a comprehensive set of demographic features.

B.

include only the demographic groups that most frequently interact with advertisements.

C.

Collect a random sample of production traffic to build the training dataset.

D.

Collect a stratified sample of production traffic to build the training dataset.

E.

Conduct fairness tests across sensitive categories and demographics on the trained model.

Question 45

You work for a manufacturing company. You need to train a custom image classification model to detect product defects at the end of an assembly line Although your model is performing well some images in your holdout set are consistently mislabeled with high confidence You want to use Vertex Al to understand your model's results What should you do?

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 46

You have recently trained a scikit-learn model that you plan to deploy on Vertex Al. This model will support both online and batch prediction. You need to preprocess input data for model inference. You want to package the model for deployment while minimizing additional code What should you do?

Options:

A.

1 Upload your model to the Vertex Al Model Registry by using a prebuilt scikit-learn prediction container

2 Deploy your model to Vertex Al Endpoints, and create a Vertex Al batch prediction job that uses the instanceConfig.inscanceType setting to transform your input data

B.

1 Wrap your model in a custom prediction routine (CPR). and build a container image from the CPR local model

2 Upload your sci-kit learn model container to Vertex Al Model Registry

3 Deploy your model to Vertex Al Endpoints, and create a Vertex Al batch prediction job

C.

1. Create a custom container for your sci-kit learn model,

2 Define a custom serving function for your model

3 Upload your model and custom container to Vertex Al Model Registry

4 Deploy your model to Vertex Al Endpoints, and create a Vertex Al batch prediction job

D.

1 Create a custom container for your sci-kit learn model.

2 Upload your model and custom container to Vertex Al Model Registry

3 Deploy your model to Vertex Al Endpoints, and create a Vertex Al batch prediction job that uses the instanceConfig. instanceType setting to transform your input data

Question 47

You work at a bank. You need to develop a credit risk model to support loan application decisions You decide to implement the model by using a neural network in TensorFlow Due to regulatory requirements, you need to be able to explain the models predictions based on its features When the model is deployed, you also want to monitor the model's performance overtime You decided to use Vertex Al for both model development and deployment What should you do?

Options:

A.

Use Vertex Explainable Al with the sampled Shapley method, and enable Vertex Al Model Monitoring to

check for feature distribution drift.

B.

Use Vertex Explainable Al with the sampled Shapley method, and enable Vertex Al Model Monitoring to

check for feature distribution skew.

C.

Use Vertex Explainable Al with the XRAI method, and enable Vertex Al Model Monitoring to check for feature distribution drift.

D.

Use Vertex Explainable Al with the XRAI method and enable Vertex Al Model Monitoring to check for feature distribution skew.

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