Question 1

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?

Options :

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

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

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

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

Answer: B

Question 2

You work for a toy manufacturer that has been experiencing a large increase in demand. You need to build an ML model to reduce the amount of time spent by quality control inspectors checking for product defects. Faster defect detection is a priority. The factory does not have reliable Wi-Fi. Your company wants to implement the new ML model as soon as possible. Which model should you use?

Options :

A : AutoML Vision Edge mobile-high-accuracy-1 model

B : AutoML Vision Edge mobile-low-latency-1 model

C : AutoML Vision model

D : AutoML Vision Edge mobile-versatile-1 model

Answer: B

Question 3

You work for a retail company. You have created a Vertex Al forecast model that produces monthly item sales predictions. You want to quickly create a report that will help to explain how the model calculates the predictions. You have one month of recent actual sales data that was not included in the training dataset. How should you generate data for your report?

Options :

A :

Create a batch prediction job by using the actual sales data Compare the predictions to the actuals in the report.

B :

Create a batch prediction job by using the actual sates data and configure the job settings to generate feature attributions. Compare the results in the report.

C :

Generate counterfactual examples by using the actual sales data Create a batch prediction job using the actual sales data and the counterfactual examples Compare the results in the report.

D :

Train another model by using the same training dataset as the original and exclude some columns. Using the actual sales data create one batch prediction job by using the new model and another one with the original model Compare the two sets of predictions in the report.

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?

Options :

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 are developing a model to identify traffic signs in images extracted from videos taken from the dashboard of a vehicle. You have a dataset of 100 000 images that were cropped to show one out of ten different traffic signs. The images have been labeled accordingly for model training and are stored in a Cloud Storage bucket You need to be able to tune the model during each training run. How should you train the model?

Options :

A : Train a model for object detection by using Vertex Al AutoML.

B : Train a model for image classification by using Vertex Al AutoML.

C :

Develop the model training code for object detection and tram a model by using Vertex Al custom training.

D :

Develop the model training code for image classification and train a model by using Vertex Al custom training

Answer: D

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