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Question 283 - Professional Machine Learning Engineer discussion

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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.

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.

Answers
A.

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.

B.

Train an image clustering model 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.

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B.

Train an image clustering model 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.

C.

Create a dataset using manually labeled images. Ingest this dataset into AutoML. Train an image classification model and deploy it to 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.

Answers
C.

Create a dataset using manually labeled images. Ingest this dataset into AutoML. Train an image classification model and deploy it to 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.

Answers
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.

Suggested answer: D

Explanation:

Cloud Vision API offers pre-trained models specialized in identifying explicit or inappropriate content. By sending a copy of each image to a Cloud Storage bucket and triggering Cloud Vision through Cloud Run, the detection of explicit content is automated with minimal development time. Vertex AI custom models require more training data and infrastructure management, while AutoML-based solutions add more complexity. Cloud Vision's existing capabilities meet the requirement effectively and are highly scalable for real-time moderation needs.

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asked 07/11/2024
ML MASANE
46 questions
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