Exam Professional Machine Learning Engineer topic 1 question 307 discussion

Actual exam question from Google's Professional Machine Learning Engineer

Question #: 307
Topic #: 1

[All Professional Machine Learning Engineer Questions]

You are an AI architect at a popular photo sharing social media platform. Your organization's content moderation team currently scans images uploaded by users and removes explicit images manually. You want to implement an AI service to automatically prevent users from uploading explicit images. What should you do?

A. Train an image clustering model by using TensorFlow in a Vertex AI Workbench instance. Deploy this model to a Vertex AI endpoint and configure it for online inference. Run this model each time a new image is uploaded to identify and block inappropriate uploads.
B. Develop a custom TensorFlow model in a Vertex AI Workbench instance. Train the model on a dataset of manually labeled images. Deploy the model to a Vertex AI endpoint. Run periodic batch inference to identify inappropriate uploads and report them to the content moderation team.
C. Create a dataset using manually labeled images. Ingest this dataset into AutoML. Train an image classification model and deploy into a Vertex AI endpoint. Integrate this endpoint with the image upload process to identify and block inappropriate uploads. Monitor predictions and periodically retrain the model.
D. Send a copy of every user-uploaded image to a Cloud Storage bucket. Configure a Cloud Run function that triggers the Cloud Vision API to detect explicit content each time a new image is uploaded. Report the classifications to the content moderation team for review.

Show Suggested Answer

Suggested Answer: C 🗳️

by ricardovazz at June 30, 2025, 6:08 p.m.

Comments

Submit Cancel

qaz09

1 month ago

Selected Answer: C

C is correct answer A --> clustering is unsupervised model, but we have labeled dataset for training, so it's better to use some supervised ML models for better accuracy B --> this one describes batch predictions and for our use case we need online predictions D --> it works after upload and the goal here is to prevent users from uploading

upvoted 1 times

...