aws-samples / aws-samples/amazon-sagemaker-ab-testing-pipeline
enhancement: Associate experiment with SageMaker project, and tuning training jobs
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- Dominant language
- Python
- Stars
- 45
- Forks
- 14
- PR merge metrics
- No merged PRs in 30d
Description
Move the code to create the sagemaker experiment after loading the project, so the experiment can be associated with the project.
Create an experiment name of project_id, with display name of project_name
Create two trials under an experiment
- Pipeline with single training job
- Tuning Job that associates all training jobs.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the code that loads the project and creates the SageMaker experiment. Confirm the experiment uses project_id and project_name, then verify that separate trials represent the single-training-job pipeline and tuning job with all training jobs associated; the issue provides no test path.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, python
- Domain
- cloud, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100