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Merge branch 'main' into release/1.9.0
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‎.github/workflows/mwaa-requirements.check.yml‎

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‎CHANGELOG.md‎

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- remove gettext-base dependency from `sagemaker-studio` module (fixes install with AL2023 base image)
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- fix add explicit boto3 dependency to `sagemaker-custom-kernels` module
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- fix missing permission causing UpdateFailed status in `sagemaker-studio` after deploying `sagemaker-custom-kernels`
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- refactored `sagemaker-templates-service-catalog` module into `sagemaker-templates-factory`
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### **Removed**
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- removed custom MWAA constraints and requirements file examples
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## v1.8.0
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‎README.md‎

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|--------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| [SageMaker Studio Module](modules/sagemaker/sagemaker-studio/README.md) | Provisions secure SageMaker Studio Domain environment, creates example User Profiles for Data Scientist and Lead Data Scientist linked to IAM Roles, and adds lifecycle config |
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| [SageMaker Endpoint Module](modules/sagemaker/sagemaker-endpoint/README.md) | Creates SageMaker real-time inference endpoint for the specified model package or latest approved model from the model package group |
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| [SageMaker Project Templates via Service Catalog Module](modules/sagemaker/sagemaker-templates-service-catalog/README.md) | Provisions SageMaker Project Templates for an organization. The templates are available using SageMaker Studio Classic or Service Catalog. Available templates:<br/> - [Train a model on Abalone dataset using XGBoost](modules/sagemaker/sagemaker-templates-service-catalog/README.md#train-a-model-on-abalone-dataset-with-xgboost-template)<br/>- [Perform batch inference](modules/sagemaker/sagemaker-templates-service-catalog/README.md#batch-inference-template)<br/>- [Multi-account model deployment](modules/sagemaker/sagemaker-templates-service-catalog/README.md#multi-account-model-deployment-template) <br/>- [HuggingFace model import template](modules/sagemaker/sagemaker-templates-service-catalog/README.md#huggingface-model-import-template) <br/>- [LLM fine-tuning and evaluation](modules/sagemaker/sagemaker-templates-service-catalog/README.md#llm-evaluate-template) |
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| [SageMaker Project Templates Factory Module](modules/sagemaker/sagemaker-templates-service-catalog/README.md) | Provisions SageMaker Project Templates for an organization based on the specified template type. Available templates:<br/> - [Train a model on Abalone dataset using XGBoost](modules/sagemaker/sagemaker-templates-service-catalog/README.md#train-a-model-on-abalone-dataset-with-xgboost-template)<br/>- [Perform batch inference](modules/sagemaker/sagemaker-templates-service-catalog/README.md#batch-inference-template)<br/>- [Multi-account model deployment](modules/sagemaker/sagemaker-templates-service-catalog/README.md#multi-account-model-deployment-template) <br/>- [HuggingFace model import template](modules/sagemaker/sagemaker-templates-service-catalog/README.md#huggingface-model-import-template) <br/>- [LLM fine-tuning and evaluation](modules/sagemaker/sagemaker-templates-service-catalog/README.md#llm-evaluate-template) |
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| [SageMaker Notebook Instance Module](modules/sagemaker/sagemaker-notebook/README.md) | Creates secure SageMaker Notebook Instance for the Data Scientist, clones the source code to the workspace |
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| [SageMaker Custom Kernel Module](modules/sagemaker/sagemaker-custom-kernel/README.md) | Builds custom kernel for SageMaker Studio from a Dockerfile |
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| [SageMaker Model Package Group Module](modules/sagemaker/sagemaker-model-package-group/README.md) | Creates a SageMaker Model Package Group to register and version SageMaker Machine Learning (ML) models and setups an Amazon EventBridge Rule to send model package group state change events to an Amazon EventBridge Bus |

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