AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 131

An ML engineer needs to train a supervised deep learning model. The available dataset is a large number of unlabeled images that only employees should access. The ML engineer needs to implement a solution that labels the dataset with the highest possible accuracy.

Which combination of steps should the ML engineer take to meet these requirements? (Choose two.)

Answer options

• A. Use Amazon Rekognition to automatically label the dataset.
• B. Train the deep learning model directly on the raw data. Let the model infer the labels by itself.
• C. Use Amazon SageMaker Ground Truth to create an annotation job that specifies the labeling task and requirements.
• D. Set up workforce teams to access a private workforce to run and review the annotation job created by Amazon SageMaker Ground Truth.
• E. Use Amazon Mechanical Turk to complete the annotation job created by Amazon SageMaker Ground Truth.

Correct answer: C, D

Explanation

The correct steps are C and D, as they involve using Amazon SageMaker Ground Truth to create a structured annotation job and setting up a private workforce to ensure the labeling task is done accurately. Option A does not provide the necessary control over the labeling process, while B relies on unassisted inference, which may lead to lower accuracy. Option E, while an option for annotation, does not align with the requirement for a private workforce.