aws / aws/sagemaker-python-sdk
Contribute example with Sagemaker SDK v3
- Dominant language
- Python
- Stars
- 2.3k
- Forks
- 1.3k
- Avg merge
- 1d 22h
- Merged PRs (30d)
- 35
Description
**Describe the feature you'd like**
Recently, the SDK has been upgraded to V3, and it still lack of hand-on example with a customized algorithm container (scikit-learn, jax,...) along with old dependencies ([sagemaker training toolkit](https://github.com/aws/sagemaker-training-toolkit/tree/master)). I've worked on a company project on using Sagemaker SDK v3 recently, and want to contribute my implementation as an example to Sagemaker SDK documentation.
**How would this feature be used? Please describe.**
This example would enhance user experience with Sagemaker SDK v3
**Describe alternatives you've considered**
The example will use 2 principles,
- Bring your own container, customize the algorithm
- Pipeline declaration(runtime, control logic) and dataflow within pipeline (Property file, S3)
Contributor guide
Research direction
The issue names no repository file, test, or example entry point; start by locating the SageMaker SDK v3 documentation examples and review the linked sagemaker-training-toolkit. Clarify the scope for the custom algorithm container and pipeline dataflow, then verify that the example covers bring-your-own-container use and runs as documented.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, python, scikit-learn
- Domain
- cloud, documentation, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100