Amazon SageMaker Service
Provides APIs for creating and managing Amazon SageMaker resources.
Other Resources:
sagemaker(config = list())
config |
Optional configuration of credentials, endpoint, and/or region. |
svc <- sagemaker(
config = list(
credentials = list(
creds = list(
access_key_id = "string",
secret_access_key = "string",
session_token = "string"
),
profile = "string"
),
endpoint = "string",
region = "string"
)
)| add_association | Creates an association between the source and the destination |
| add_tags | Adds or overwrites one or more tags for the specified Amazon SageMaker resource |
| associate_trial_component | Associates a trial component with a trial |
| create_action | Creates an action |
| create_algorithm | Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS Marketplace |
| create_app | Creates a running App for the specified UserProfile |
| create_app_image_config | Creates a configuration for running a SageMaker image as a KernelGateway app |
| create_artifact | Creates an artifact |
| create_auto_ml_job | Creates an Autopilot job |
| create_code_repository | Creates a Git repository as a resource in your Amazon SageMaker account |
| create_compilation_job | Starts a model compilation job |
| create_context | Creates a context |
| create_data_quality_job_definition | Creates a definition for a job that monitors data quality and drift |
| create_device_fleet | Creates a device fleet |
| create_domain | Creates a Domain used by Amazon SageMaker Studio |
| create_edge_packaging_job | Starts a SageMaker Edge Manager model packaging job |
| create_endpoint | Creates an endpoint using the endpoint configuration specified in the request |
| create_endpoint_config | Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models |
| create_experiment | Creates an SageMaker experiment |
| create_feature_group | Create a new FeatureGroup |
| create_flow_definition | Creates a flow definition |
| create_human_task_ui | Defines the settings you will use for the human review workflow user interface |
| create_hyper_parameter_tuning_job | Starts a hyperparameter tuning job |
| create_image | Creates a custom SageMaker image |
| create_image_version | Creates a version of the SageMaker image specified by ImageName |
| create_labeling_job | Creates a job that uses workers to label the data objects in your input dataset |
| create_model | Creates a model in Amazon SageMaker |
| create_model_bias_job_definition | Creates the definition for a model bias job |
| create_model_explainability_job_definition | Creates the definition for a model explainability job |
| create_model_package | Creates a model package that you can use to create Amazon SageMaker models or list on AWS Marketplace, or a versioned model that is part of a model group |
| create_model_package_group | Creates a model group |
| create_model_quality_job_definition | Creates a definition for a job that monitors model quality and drift |
| create_monitoring_schedule | Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint |
| create_notebook_instance | Creates an Amazon SageMaker notebook instance |
| create_notebook_instance_lifecycle_config | Creates a lifecycle configuration that you can associate with a notebook instance |
| create_pipeline | Creates a pipeline using a JSON pipeline definition |
| create_presigned_domain_url | Creates a URL for a specified UserProfile in a Domain |
| create_presigned_notebook_instance_url | Returns a URL that you can use to connect to the Jupyter server from a notebook instance |
| create_processing_job | Creates a processing job |
| 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 |
| create_training_job | Starts a model training job |
| create_transform_job | Starts a transform job |
| create_trial | Creates an Amazon SageMaker trial |
| create_trial_component | Creates a trial component, which is a stage of a machine learning trial |
| create_user_profile | Creates a user profile |
| create_workforce | Use this operation to create a workforce |
| create_workteam | Creates a new work team for labeling your data |
| delete_action | Deletes an action |
| delete_algorithm | Removes the specified algorithm from your account |
| delete_app | Used to stop and delete an app |
| delete_app_image_config | Deletes an AppImageConfig |
| delete_artifact | Deletes an artifact |
| delete_association | Deletes an association |
| delete_code_repository | Deletes the specified Git repository from your account |
| delete_context | Deletes an context |
| delete_data_quality_job_definition | Deletes a data quality monitoring job definition |
| delete_device_fleet | Deletes a fleet |
| delete_domain | Used to delete a domain |
| delete_endpoint | Deletes an endpoint |
| delete_endpoint_config | Deletes an endpoint configuration |
| delete_experiment | Deletes an Amazon SageMaker experiment |
| delete_feature_group | Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup |
| delete_flow_definition | Deletes the specified flow definition |
| delete_human_task_ui | Use this operation to delete a human task user interface (worker task template) |
| delete_image | Deletes a SageMaker image and all versions of the image |
| delete_image_version | Deletes a version of a SageMaker image |
| delete_model | Deletes a model |
| delete_model_bias_job_definition | Deletes an Amazon SageMaker model bias job definition |
| delete_model_explainability_job_definition | Deletes an Amazon SageMaker model explainability job definition |
| delete_model_package | Deletes a model package |
| delete_model_package_group | Deletes the specified model group |
| delete_model_package_group_policy | Deletes a model group resource policy |
| delete_model_quality_job_definition | Deletes the secified model quality monitoring job definition |
| delete_monitoring_schedule | Deletes a monitoring schedule |
| delete_notebook_instance | Deletes an Amazon SageMaker notebook instance |
| delete_notebook_instance_lifecycle_config | Deletes a notebook instance lifecycle configuration |
| delete_pipeline | Deletes a pipeline if there are no in-progress executions |
| delete_project | Delete the specified project |
| delete_tags | Deletes the specified tags from an Amazon SageMaker resource |
| delete_trial | Deletes the specified trial |
| delete_trial_component | Deletes the specified trial component |
| delete_user_profile | Deletes a user profile |
| delete_workforce | Use this operation to delete a workforce |
| delete_workteam | Deletes an existing work team |
| deregister_devices | Deregisters the specified devices |
| describe_action | Describes an action |
| describe_algorithm | Returns a description of the specified algorithm that is in your account |
| describe_app | Describes the app |
| describe_app_image_config | Describes an AppImageConfig |
| describe_artifact | Describes an artifact |
| describe_auto_ml_job | Returns information about an Amazon SageMaker job |
| describe_code_repository | Gets details about the specified Git repository |
| describe_compilation_job | Returns information about a model compilation job |
| describe_context | Describes a context |
| describe_data_quality_job_definition | Gets the details of a data quality monitoring job definition |
| describe_device | Describes the device |
| describe_device_fleet | A description of the fleet the device belongs to |
| describe_domain | The description of the domain |
| describe_edge_packaging_job | A description of edge packaging jobs |
| describe_endpoint | Returns the description of an endpoint |
| describe_endpoint_config | Returns the description of an endpoint configuration created using the CreateEndpointConfig API |
| describe_experiment | Provides a list of an experiment's properties |
| describe_feature_group | Use this operation to describe a FeatureGroup |
| describe_flow_definition | Returns information about the specified flow definition |
| describe_human_task_ui | Returns information about the requested human task user interface (worker task template) |
| describe_hyper_parameter_tuning_job | Gets a description of a hyperparameter tuning job |
| describe_image | Describes a SageMaker image |
| describe_image_version | Describes a version of a SageMaker image |
| describe_labeling_job | Gets information about a labeling job |
| describe_model | Describes a model that you created using the CreateModel API |
| describe_model_bias_job_definition | Returns a description of a model bias job definition |
| describe_model_explainability_job_definition | Returns a description of a model explainability job definition |
| describe_model_package | Returns a description of the specified model package, which is used to create Amazon SageMaker models or list them on AWS Marketplace |
| describe_model_package_group | Gets a description for the specified model group |
| describe_model_quality_job_definition | Returns a description of a model quality job definition |
| describe_monitoring_schedule | Describes the schedule for a monitoring job |
| describe_notebook_instance | Returns information about a notebook instance |
| describe_notebook_instance_lifecycle_config | Returns a description of a notebook instance lifecycle configuration |
| describe_pipeline | Describes the details of a pipeline |
| describe_pipeline_definition_for_execution | Describes the details of an execution's pipeline definition |
| describe_pipeline_execution | Describes the details of a pipeline execution |
| describe_processing_job | Returns a description of a processing job |
| describe_project | Describes the details of a project |
| describe_subscribed_workteam | Gets information about a work team provided by a vendor |
| describe_training_job | Returns information about a training job |
| describe_transform_job | Returns information about a transform job |
| describe_trial | Provides a list of a trial's properties |
| describe_trial_component | Provides a list of a trials component's properties |
| describe_user_profile | Describes a user profile |
| describe_workforce | Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs) |
| describe_workteam | Gets information about a specific work team |
| disable_sagemaker_servicecatalog_portfolio | Disables using Service Catalog in SageMaker |
| disassociate_trial_component | Disassociates a trial component from a trial |
| enable_sagemaker_servicecatalog_portfolio | Enables using Service Catalog in SageMaker |
| get_device_fleet_report | Describes a fleet |
| get_model_package_group_policy | Gets a resource policy that manages access for a model group |
| get_sagemaker_servicecatalog_portfolio_status | Gets the status of Service Catalog in SageMaker |
| get_search_suggestions | An auto-complete API for the search functionality in the Amazon SageMaker console |
| list_actions | Lists the actions in your account and their properties |
| list_algorithms | Lists the machine learning algorithms that have been created |
| list_app_image_configs | Lists the AppImageConfigs in your account and their properties |
| list_apps | Lists apps |
| list_artifacts | Lists the artifacts in your account and their properties |
| list_associations | Lists the associations in your account and their properties |
| list_auto_ml_jobs | Request a list of jobs |
| list_candidates_for_auto_ml_job | List the Candidates created for the job |
| list_code_repositories | Gets a list of the Git repositories in your account |
| list_compilation_jobs | Lists model compilation jobs that satisfy various filters |
| list_contexts | Lists the contexts in your account and their properties |
| list_data_quality_job_definitions | Lists the data quality job definitions in your account |
| list_device_fleets | Returns a list of devices in the fleet |
| list_devices | A list of devices |
| list_domains | Lists the domains |
| list_edge_packaging_jobs | Returns a list of edge packaging jobs |
| list_endpoint_configs | Lists endpoint configurations |
| list_endpoints | Lists endpoints |
| list_experiments | Lists all the experiments in your account |
| list_feature_groups | List FeatureGroups based on given filter and order |
| list_flow_definitions | Returns information about the flow definitions in your account |
| list_human_task_uis | Returns information about the human task user interfaces in your account |
| list_hyper_parameter_tuning_jobs | Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account |
| list_images | Lists the images in your account and their properties |
| list_image_versions | Lists the versions of a specified image and their properties |
| list_labeling_jobs | Gets a list of labeling jobs |
| list_labeling_jobs_for_workteam | Gets a list of labeling jobs assigned to a specified work team |
| list_model_bias_job_definitions | Lists model bias jobs definitions that satisfy various filters |
| list_model_explainability_job_definitions | Lists model explainability job definitions that satisfy various filters |
| list_model_package_groups | Gets a list of the model groups in your AWS account |
| list_model_packages | Lists the model packages that have been created |
| list_model_quality_job_definitions | Gets a list of model quality monitoring job definitions in your account |
| list_models | Lists models created with the CreateModel API |
| list_monitoring_executions | Returns list of all monitoring job executions |
| list_monitoring_schedules | Returns list of all monitoring schedules |
| list_notebook_instance_lifecycle_configs | Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API |
| list_notebook_instances | Returns a list of the Amazon SageMaker notebook instances in the requester's account in an AWS Region |
| list_pipeline_executions | Gets a list of the pipeline executions |
| list_pipeline_execution_steps | Gets a list of PipeLineExecutionStep objects |
| list_pipeline_parameters_for_execution | Gets a list of parameters for a pipeline execution |
| list_pipelines | Gets a list of pipelines |
| list_processing_jobs | Lists processing jobs that satisfy various filters |
| list_projects | Gets a list of the projects in an AWS account |
| list_subscribed_workteams | Gets a list of the work teams that you are subscribed to in the AWS Marketplace |
| list_tags | Returns the tags for the specified Amazon SageMaker resource |
| list_training_jobs | Lists training jobs |
| list_training_jobs_for_hyper_parameter_tuning_job | Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched |
| list_transform_jobs | Lists transform jobs |
| list_trial_components | Lists the trial components in your account |
| list_trials | Lists the trials in your account |
| list_user_profiles | Lists user profiles |
| list_workforces | Use this operation to list all private and vendor workforces in an AWS Region |
| list_workteams | Gets a list of private work teams that you have defined in a region |
| put_model_package_group_policy | Adds a resouce policy to control access to a model group |
| register_devices | Register devices |
| render_ui_template | Renders the UI template so that you can preview the worker's experience |
| search | Finds Amazon SageMaker resources that match a search query |
| start_monitoring_schedule | Starts a previously stopped monitoring schedule |
| start_notebook_instance | Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume |
| start_pipeline_execution | Starts a pipeline execution |
| stop_auto_ml_job | A method for forcing the termination of a running job |
| stop_compilation_job | Stops a model compilation job |
| stop_edge_packaging_job | Request to stop an edge packaging job |
| stop_hyper_parameter_tuning_job | Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched |
| stop_labeling_job | Stops a running labeling job |
| stop_monitoring_schedule | Stops a previously started monitoring schedule |
| stop_notebook_instance | Terminates the ML compute instance |
| stop_pipeline_execution | Stops a pipeline execution |
| stop_processing_job | Stops a processing job |
| stop_training_job | Stops a training job |
| stop_transform_job | Stops a transform job |
| update_action | Updates an action |
| update_app_image_config | Updates the properties of an AppImageConfig |
| update_artifact | Updates an artifact |
| update_code_repository | Updates the specified Git repository with the specified values |
| update_context | Updates a context |
| update_device_fleet | Updates a fleet of devices |
| update_devices | Updates one or more devices in a fleet |
| update_domain | Updates the default settings for new user profiles in the domain |
| update_endpoint | Deploys the new EndpointConfig specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous EndpointConfig (there is no availability loss) |
| update_endpoint_weights_and_capacities | Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint |
| update_experiment | Adds, updates, or removes the description of an experiment |
| update_image | Updates the properties of a SageMaker image |
| update_model_package | Updates a versioned model |
| update_monitoring_schedule | Updates a previously created schedule |
| update_notebook_instance | Updates a notebook instance |
| update_notebook_instance_lifecycle_config | Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API |
| update_pipeline | Updates a pipeline |
| update_pipeline_execution | Updates a pipeline execution |
| update_training_job | Update a model training job to request a new Debugger profiling configuration |
| update_trial | Updates the display name of a trial |
| update_trial_component | Updates one or more properties of a trial component |
| update_user_profile | Updates a user profile |
| update_workforce | Use this operation to update your workforce |
| update_workteam | Updates an existing work team with new member definitions or description |
## Not run: svc <- sagemaker() svc$add_association( Foo = 123 ) ## End(Not run)
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