Q31 — AWS SAA-C03 Ch.12

Question 31 of 100 | ← Chapter 12

Q831. A company needs a solution to prevent photos with unwanted content from being uploaded to the company's web application. The solution must not involve training a machine learning (ML) model.Which solution will meet these requirements?

• A. Create and deploy a model by using Amazon SageMaker Autopilot. Create a real-time endpoint that the web application invokes when new photos are uploaded.
• B. 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. ✓
• C. Create an Amazon CloudFront function that uses Amazon Comprehend to detect unwanted content.Associate the function with the web application.
• D. Create an AWS Lambda function that uses Amazon Rekognition Video to detect unwanted content.Create a Lambda function URL that the web application invokes when new photos are uploaded.

Correct Answer: B. 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.

Explanation

The solution that will meet the requirements of preventing photos with unwanted content from being uploaded to the company's web application without training a machine learning (ML) model is option B: 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.To prevent unwanted content from being uploaded to the web application without training an ML model, you can follow these steps:Step 1: Create an AWS Lambda function (Option B)AWS Lambda allows you to run code without provisioning or managing servers. By creating a Lambda function, you can write code that uses Amazon Rekognition to analyze the uploaded photos and detect unwanted content.Step 2: Use Amazon Rekognition to detect unwanted content (Option B)Amazon Rekognition is a deep learning-based image and video analysis service. By invoking the Rekognition API within your Lambda function, you can leverage its pre-trained models to detect and identify unwanted content in the uploaded photos.Step 3: Create a Lambda function URL for the web application (Option B)Once the Lambda function is created and configured to use Amazon Rekognition, you can generate a unique Lambda function URL. The web application can then invoke this URL whenever new photos are uploaded for content analysis.Option A suggests creating and deploying a model using Amazon SageMaker Autopilot. While SageMaker Autopilot is a powerful tool for automatically building ML models, it involves training a model, which is not a requirement in this scenario.Option C suggests creating an Amazon CloudFront function that uses Amazon Comprehend to detect unwanted content. However, CloudFront functions are primarily used for modifying HTTP requests and responses at the edge locations of the CloudFront content delivery network and may not be directly applicable for content analysis.Option D suggests using Amazon Rekognition Video to detect unwanted content. However, Rekognition Video is specifically designed for analyzing video content, and using it for static photos may not be the most suitable solution.Therefore, option B is the most appropriate solution as it leverages an AWS Lambda function with Amazon Rekognition to detect unwanted content in the uploaded photos, providing an efficient and effective solution without the need to train an ML model.