Question 9
Domain 1: Data Preparation for Machine Learning (ML)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.)
Correct answer: C
Explanation
A supervised deep learning model requires labeled training data, so the unlabeled images must be annotated before training. Because the dataset is restricted to employees, the engineer should use a secure, access-controlled labeling workflow and choose a high-accuracy labeling method such as human review or active labeling to produce the best labels.
Why each option is right or wrong
A. Use Amazon SageMaker Ground Truth to create an annotation job that specifies the labeling task and requirements.
Ground Truth creates the labeling workflow, but alone does not enforce employee-only annotators.
B. Set up workforce teams to access a private workforce to run and review the annotation job created by Amazon SageMaker Ground Truth.
A private workforce supplies employee annotators, but needs a Ground Truth labeling job to perform labeling.
C. All of the above
Each of the listed options is a valid answer; all are needed.