Which combination of actions will meet these requirements with the LEAST operational overhead?
(Choose two.)
Use SageMaker Clarify to automatically detect data bias
Turn on the bias detection option in SageMaker Ground Truth to automatically analyze data features.
Use SageMaker Model Monitor to generate a bias drift report.
Configure SageMaker Data Wrangler to generate a bias report.
Use SageMaker Experiments to perform a data check
Explanations:
SageMaker Clarify provides tools for detecting and mitigating bias in datasets and machine learning models. It can automatically detect bias in the dataset before model training, minimizing manual effort.
SageMaker Ground Truth focuses on data labeling, and while it can be used for data annotation tasks, it does not automatically perform bias detection on data features.
SageMaker Model Monitor is used for monitoring model performance and drift after deployment, not for detecting bias in training data before model development.
SageMaker Data Wrangler can be used to preprocess and analyze data, including generating reports that may help in identifying potential biases within the dataset.
SageMaker Experiments is designed for managing machine learning experiments and tracking models, but it does not directly provide functionality for bias detection in data.
I plot that the answer is:
Use SageMaker Clarify to automatically detect data bias