A company needs to prevent photos containing unwanted content from being uploaded to its web application. The solution must not involve training an ML model. Which solution meets these requirements?
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Correct answer: Create an AWS Lambda function that uses Amazon Rekognition to detect unwanted content. Create a Lambda function URL that the web application invokes when new photos are uploaded..
Why this is the answer
The correct solution uses Amazon Rekognition, a service specifically designed for image and video analysis, to detect unwanted content without requiring custom ML model training. An AWS Lambda function provides the serverless compute environment to execute the Rekognition API calls, and a Lambda function URL offers a simple HTTP(S) endpoint for the web application to invoke synchronously when new photos are uploaded. Incorrect options: SageMaker Autopilot is for training custom ML models, which the requirement explicitly states to avoid. Amazon Comprehend is for natural language processing (text analysis), not image analysis. Amazon Rekognition Video is for video analysis, not static images. While Rekognition can analyze both, the general Rekognition service is sufficient for static images, and Rekognition Video implies a focus on video streams.
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