Exam Professional Machine Learning Engineer topic 1 question 274 discussion

Actual exam question from Google's Professional Machine Learning Engineer

Question #: 274
Topic #: 1

[All Professional Machine Learning Engineer Questions]

You are training and deploying updated versions of a regression model with tabular data by using Vertex AI Pipelines, Vertex AI Training, Vertex AI Experiments, and Vertex AI Endpoints. The model is deployed in a Vertex AI endpoint, and your users call the model by using the Vertex AI 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?

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.

Show Suggested Answer

Suggested Answer: A 🗳️

by pikachu007 at Jan. 13, 2024, 4:42 p.m.

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CHARLIE2108

10 months, 2 weeks ago

Selected Answer: A

I went with A

upvoted 3 times

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daidai75

11 months ago

Selected Answer: A

Vertex AI Model Monitoring is specifically designed for this purpose and provides out-of-the-box functionality for monitoring the data distribution of your model's predictions. It can automatically detect drift and trigger alerts based on predefined thresholds, making it the most efficient and straightforward solution. Option B,C and D are either over complex or too many manual operations.

upvoted 1 times

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b1a8fae

11 months ago

Selected Answer: A

https://cloud.google.com/blog/topics/developers-practitioners/monitor-models-training-serving-skew-vertex-ai

upvoted 1 times

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36bdc1e

11 months, 1 week ago

A Prediction drift is the change in the distribution of feature values or labels over time.

upvoted 1 times

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pikachu007

11 months, 1 week ago

Selected Answer: A

Options B and C: While Cloud Logging and Cloud Monitoring can be used for general monitoring, they don't have the same specialized focus on prediction drift, potentially requiring more complex setup and analysis. Option D: Exporting logs to BigQuery and creating a Cloud Function for analysis can be time-consuming and less efficient compared to Vertex AI Model Monitoring's out-of-the-box capabilities.

upvoted 1 times

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