MLS-C01 Question #231: Real Exam Question with Answer & Explanation

Question

An ecommerce company wants to train a large image classification model with 10,000 classes. The company runs multiple model training iterations and needs to minimize operational overhead and cost. The company also needs to avoid loss of work and model retraining. Which solution will meet these requirements?

Options

• ACreate the training jobs as AWS Batch jobs that use Amazon EC2 Spot Instances in a managed
• BUse Amazon EC2 Spot Instances to run the training jobs. Use a Spot Instance interruption notice
• CUse AWS Lambda to run the training jobs. Save model weights to Amazon S3.
• DUse managed spot training in Amazon SageMaker. Launch the training jobs with checkpointing

Explanation

https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html Managed spot training can optimize the cost of training models up to 90% over on-demand instances. SageMaker manages the Spot interruptions on your behalf. "Spot instances can be interrupted, causing jobs to take longer to start or finish. You can configure your managed spot training job to use checkpoints. SageMaker copies checkpoint data from a local path to Amazon S3. When the job is restarted, SageMaker copies the data from Amazon S3 back into the local path. The training job can then resume from the last checkpoint instead of restarting."

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