AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 163
A company is using an ML model to classify motion in videos. The data is stored in MP4 format in Amazon S3. When the company created the model, the company needed 4 months to label all the video frames.
The company needs to retrain the model with an existing training workflow in Amazon SageMaker AI. An ML engineer must implement a solution that decreases the labeling time.
Which solution will meet these requirements?
Answer options
- A. Use SageMaker Ground Truth to annotate the video frames.
- B. Use SageMaker JumpStart to use pre-trained computer vision models to develop a labeling model.
- C. Use SageMaker Data Wrangler to create a data workflow. Use the workflow to optimize the labeling process.
- D. Use the labeling interface of Amazon Augmented AI (Amazon A2I) with Amazon Rekognition to label the video frames.
Correct answer: D
Explanation
The correct answer is D because Amazon Augmented AI (Amazon A2I) combined with Amazon Rekognition provides an efficient way to automate and assist in the labeling of video frames, significantly reducing the time required. Options A, B, and C may enhance the process but do not specifically address the need for a solution that directly decreases labeling time as effectively as option D.