Comments (3)
I completely agree. Greater transparency is necessary. I sense that this repository functions more as "source available" rather than truly open source.
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cc @ShwetaSingh801.
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I think I found place better suited to request SageMaker features that are wider in scope than just the Python SDK: https://github.com/aws/amazon-sagemaker-feedback. In less than a year, they already shipped a couple of features requested by users 🥳. Maybe this repo could point to it?
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Related Issues (20)
- Feature Store Data Lineage and Associated Executions HOT 1
- Inconsistent Versioning of transformers_version
- SageMaker Processing Job doesn't support FastFile Input Mode
- "AttributeError: 'NoneType' object has no attribute 'len'" when deploying inference component
- Cant see evaluation metrics in new SageMaker Studio UI after doing model.register HOT 9
- Incorrect BiasConfig type hint for `label_values_or_threshold`
- How to recreate the predictor variable from the endpoint_name if somehow the variable is lost?
- No DataProcessing in local transform job HOT 1
- Update documentation to use `sagemaker-python-sdk` as opposed to `sagemaker` HOT 3
- Fix documentation of FeatureGroup HOT 1
- Sagemaker Local-Mode permission errors
- ModelStep name includes "-RegisterModel" suffix HOT 1
- Tags are't inherited from the `sagemaker_config` to hyperparameter tuning requests
- ValueError: Invalid explanations value when creating ModelCard from ModelPackage
- AsyncPredictor fails if name is None, despite it being the default
- Newline chars are not supported in sagemaker feature store string types
- SageMaker Batch currently doesn't support Model entity with container definitions which use ModelDataSource attribute
- 'base_job_name' parameter is not used to name the Processing Jobs that are created by the Model Monitoring Schedule
- (AutoMLV2) UnboundLocalError: local variable 'input_config' referenced before assignment
- Import/get data from bigquery
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