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Google Updated Professional-Machine-Learning-Engineer Exam Questions and Answers by malachi

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Google Professional-Machine-Learning-Engineer Exam Overview :

Exam Name: Google Professional Machine Learning Engineer
Exam Code: Professional-Machine-Learning-Engineer Dumps
Vendor: Google Certification: Machine Learning Engineer
Questions: 285 Q&A's Shared By: malachi
Question 68

You work for an online retailer. Your company has a few thousand short lifecycle products. Your company has five years of sales data stored in BigQuery. You have been asked to build a model that will make monthly sales predictions for each product. You want to use a solution that can be implemented quickly with minimal effort. What should you do?

Options:

A.

Use Prophet on Vertex Al Training to build a custom model.

B.

Use Vertex Al Forecast to build a NN-based model.

C.

Use BigQuery ML to build a statistical AR1MA_PLUS model.

D.

Use TensorFlow on Vertex Al Training to build a custom model.

Discussion
Question 69

You are building a real-time prediction engine that streams files which may contain Personally Identifiable Information (Pll) to Google Cloud. You want to use the Cloud Data Loss Prevention (DLP) API to scan the files. How should you ensure that the Pll is not accessible by unauthorized individuals?

Options:

A.

Stream all files to Google CloudT and then write the data to BigQuery Periodically conduct a bulk scan of the table using the DLP API.

B.

Stream all files to Google Cloud, and write batches of the data to BigQuery While the data is being written to BigQuery conduct a bulk scan of the data using the DLP API.

C.

Create two buckets of data Sensitive and Non-sensitive Write all data to the Non-sensitive bucket Periodically conduct a bulk scan of that bucket using the DLP API, and move the sensitive data to the Sensitive bucket

D.

Create three buckets of data: Quarantine, Sensitive, and Non-sensitive Write all data to the Quarantine bucket.

E.

Periodically conduct a bulk scan of that bucket using the DLP API, and move the data to either the Sensitive or Non-Sensitive bucket

Discussion
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Question 70

You built and manage a production system that is responsible for predicting sales numbers. Model accuracy is crucial, because the production model is required to keep up with market changes. Since being deployed to production, the model hasn't changed; however the accuracy of the model has steadily deteriorated. What issue is most likely causing the steady decline in model accuracy?

Options:

A.

Poor data quality

B.

Lack of model retraining

C.

Too few layers in the model for capturing information

D.

Incorrect data split ratio during model training, evaluation, validation, and test

Discussion
Question 71

You are training and deploying updated versions of a regression model with tabular data by using Vertex Al Pipelines. Vertex Al Training Vertex Al Experiments and Vertex Al Endpoints. The model is deployed in a Vertex Al endpoint and your users call the model by using the Vertex Al endpoint. You want to receive an email when the feature data distribution changes significantly, so you can retrigger the training pipeline and deploy an updated version of your model What should you do?

Options:

A.

Use Vertex Al Model Monitoring Enable prediction drift monitoring on the endpoint. and specify a notification email.

B.

In Cloud Logging, create a logs-based alert using the logs in the Vertex Al endpoint. Configure Cloud Logging to send an email when the alert is triggered.

C.

In Cloud Monitoring create a logs-based metric and a threshold alert for the metric. Configure Cloud Monitoring to send an email when the alert is triggered.

D.

Export the container logs of the endpoint to BigQuery Create a Cloud Function to run a SQL query over the exported logs and send an email. Use Cloud Scheduler to trigger the Cloud Function.

Discussion
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