MLA-C01 · Question #48
MLA-C01 Question #48: Real Exam Question with Answer & Explanation
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Question
An ML engineer is using a training job to fine-tune a deep learning model in Amazon SageMaker Studio. The ML engineer previously used the same pre-trained model with a similar dataset. The ML engineer expects vanishing gradient, underutilized GPU, and overfitting problems. The ML engineer needs to implement a solution to detect these issues and to react in predefined ways when the issues occur. The solution also must provide comprehensive real-time metrics during the training. Which solution will meet these requirements with the LEAST operational overhead?
Options
- AUse TensorBoard to monitor the training job. Publish the findings to an Amazon Simple
- BUse Amazon CloudWatch default metrics to gain insights about the training job. Use the metrics
- CExpand the metrics in Amazon CloudWatch to include the gradients in each training step. Use the
- DUse SageMaker Debugger built-in rules to monitor the training job. Configure the rules to initiate
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