aws / aws/sagemaker-python-sdk

Contribute example with Sagemaker SDK v3

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#5,567 1 comment 0 reactions 0 assignees View on GitHub
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

Open the contributing 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

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