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
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.
sagemaker_create_project(ProjectName, ProjectDescription, ServiceCatalogProvisioningDetails, Tags)
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. For information, see What is AWS Service Catalog. |
Tags |
An array of key-value pairs that you want to use to organize and track your AWS resource costs. For more information, see Tagging AWS resources in the AWS General Reference Guide. |
A list with the following syntax:
list( ProjectArn = "string", ProjectId = "string" )
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"
)
)
)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.