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A company is creating a model to label credit card transactions.

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A company is creating a model to label credit card transactions. The company has a large volume of sample transaction data to train the model. Most of the transaction data is unlabeled. The data does not contain confidential information. The company needs to obtain labeled sample data to fine-tune the model.

A.

Run batch inference jobs on the unlabeled data

B.

Run an Amazon SageMaker AI training job that uses the PyTorch Distributed library to label data

C.

Use an Amazon SageMaker Ground Truth labeling job with Amazon Mechanical Turk workers

D.

Use an optical character recognition model trained on labeled samples to label unlabeled samples

E.

Run an Amazon SageMaker AI labeling job

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