- Lab
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Run a Managed Training Job with Amazon SageMaker
In this hands-on lab, you will learn how to run a fully managed machine learning training job with Amazon SageMaker AI. Starting from a prepared dataset in Amazon S3 and a pre-configured execution role, you will configure and launch a managed training job using a built-in algorithm, monitor it through to completion, and validate that the trained model artifact is written back to Amazon S3. This workflow allows for training models on SageMaker-managed infrastructure without provisioning or maintaining your own training compute resources.
Lab Info
Table of Contents
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Challenge
Inspect the training prerequisites
- Review the prepared dataset in the S3 input/ prefix.
- Review the SageMaker execution role in the
IAMconsole and confirm it can read the input data and write to the output/ prefix.
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Challenge
Configure and start the managed training job
- From the
Amazon SageMaker AIconsole, create anxgboosttraining job using the enforced exact nameglobomantics-xgboost-training. - Select the built-in algorithm training image; set the input S3 URI (
s3://{FULL BUCKET NAME}/input/), the output S3 URI (s3://{FULL BUCKET NAME}/output/), the execution role, and a minimum-size CPU training instance. - Adjust the training job hyperparameters for multiclass classification. Note that there are
3classes in the lab's dataset. The number of training rounds should also be set to10. - Start the job.
- From the
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Challenge
Monitor the training job
- Track the job status from InProgress through to Completed.
- Review the job’s CloudWatch logs and training metrics.
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Challenge
Validate the model artifact in S3
- Return to S3, and view the contents of the output/ prefix.
- Confirm a
model.tar.gzartifact was written under the enforced output prefix. It should look likes3://{FULL_BUCKET_NAME}/output/globomantics-xgboost-training/output/model.tar.gz.
Real skill practice before real-world application
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Turn time into mastery
On average, you retain 75% more of your learning if you take time to practice. Hands-on labs set you up for success to make those skills stick.