Use the Amazon sagemaker connector to build, train, and deploy ML models.
Integrating your application with Amazon sagemaker lets you use these operations in an automation. It exposes 6 actions, listed below. Add the connector from the Connections area, authenticate, then select its operations in the automation builder. Capabilities: actions.
Authentication
Before you begin, make sure you have the following information:
Connection Name: Choose a meaningful name for your connection. This name helps you identify the connection within your application or integration settings.
Authentication Type: The authentication method for this connector is defined in the connection setup. Select the connector in the Connections area to see the fields it requires.
Actions
Action Name | Description |
|---|---|
Create autoML job | Create autoML job in amazon sagemaker |
Describe autoML job | Describe autoML job in amazon sagemaker |
Invoke endpoint | Invoke a deployed SageMaker endpoint to get inferences from a hosted model. |
Invoke endpoint (Streaming) | Invoke a deployed SageMaker endpoint and receive the inference response as a stream. |
Invoke endpoint with JSON response stream (Streaming) | Invoke a deployed SageMaker endpoint and receive the inference response as a JSON stream. |
Search autoML job | Search autoML job in amazon sagemaker |