Create Project

sagemaker_create_project

R Documentation

Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model¶

Description¶

Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.

Usage¶

sagemaker_create_project(ProjectName, ProjectDescription,
  ServiceCatalogProvisioningDetails, Tags)

Arguments¶

ProjectName: [required] The name of the project.
ProjectDescription: A description for the project.
ServiceCatalogProvisioningDetails: [required] The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
Tags: An array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.

Value¶

A list with the following syntax:

list(
  ProjectArn = "string",
  ProjectId = "string"
)

Request syntax¶

svc$create_project(
  ProjectName = "string",
  ProjectDescription = "string",
  ServiceCatalogProvisioningDetails = list(
    ProductId = "string",
    ProvisioningArtifactId = "string",
    PathId = "string",
    ProvisioningParameters = list(
      list(
        Key = "string",
        Value = "string"
      )
    )
  ),
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)