aws sagemaker create-project
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
Options
| Name | Description |
|---|---|
--project-name <string> | The name of the project |
--project-description <string> | A description for the project |
--service-catalog-provisioning-details <structure> | The product ID and provisioning artifact ID to provision a service catalog. For information, see What is AWS Service Catalog |
--tags <list> | 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 |
--cli-input-json <string> | Performs service operation based on the JSON string provided. The JSON string follows the format provided by ``--generate-cli-skeleton``. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally |
--generate-cli-skeleton <string> | Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value ``input``, prints a sample input JSON that can be used as an argument for ``--cli-input-json``. If provided with the value ``output``, it validates the command inputs and returns a sample output JSON for that command |