sagemaker_create_endpoint: Creates an endpoint using the endpoint configuration...
In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

sagemaker_create_endpoint

R Documentation

Creates an endpoint using the endpoint configuration specified in the request

Description

Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the create_endpoint_config API.

See https://www.paws-r-sdk.com/docs/sagemaker_create_endpoint/ for full documentation.

Usage

sagemaker_create_endpoint(
  EndpointName,
  EndpointConfigName,
  DeploymentConfig = NULL,
  Tags = NULL
)

Arguments

`EndpointName`	[required] The name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in `create_endpoint`, but the case is preserved and must be matched in InvokeEndpoint.
`EndpointConfigName`	[required] The name of an endpoint configuration. For more information, see `create_endpoint_config`.
`DeploymentConfig`
`Tags`	An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.