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Upd readme with new modules
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@lccasagrande
lccasagrande committed May 3, 2024
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Expand Up @@ -23,13 +23,15 @@ See deployment steps in the [Deployment Guide](DEPLOYMENT.md).

### SageMaker Modules

| Type | Description |
|---------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [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 |
| [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 |
| Type | Description |
|---------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [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 |
| [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 |
| [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) |
| [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 |
| [SageMaker Custom Kernel Module](modules/sagemaker/sagemaker-custom-kernel/README.md) | Builds custom kernel for SageMaker Studio from a Dockerfile |
| [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 |
| [SageMaker Custom Kernel Module](modules/sagemaker/sagemaker-custom-kernel/README.md) | Builds custom kernel for SageMaker Studio from a Dockerfile |
| [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 |
| [SageMaker Model Package Promote Pipeline Module](modules/sagemaker/sagemaker-model-package-promote-pipeline/README.md) | Deploy a Pipeline to promote SageMaker Model Packages in a multi-account setup. The pipeline can be triggered through an EventBridge rule in reaction of a SageMaker Model Package Group state event change (Approved/Rejected). Once the pipeline is triggered, it will promote the latest approved model package, if one is found. |


### Mlflow Modules
Expand All @@ -56,3 +58,9 @@ See deployment steps in the [Deployment Guide](DEPLOYMENT.md).
### Industry Data Framework (IDF) Modules

The modules in this repository are compatible with [Industry Data Framework (IDF) Modules](https://github.com/awslabs/idf-modules) and can be used together within the same deployment. Refer to `examples/manifests` for examples.

### Events Modules

| Type | Description |
|-------------------------------------------------------------------------|------------------------------------------------------------------------|
| [Event Bus Module](modules/examples/events/event-busREADME.md) | Creates an Amazon EventBridge Bus for cross-account events. |

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