paws (version 0.1.12)

personalize: Amazon Personalize

Description

Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.

Usage

personalize(config = list())

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Arguments

config

Optional configuration of credentials, endpoint, and/or region.

Service syntax

svc <- personalize(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string"
    ),
    endpoint = "string",
    region = "string"
  )
)

Operations

create_batch_inference_job	Creates a batch inference job
create_campaign	Creates a campaign by deploying a solution version
create_dataset	Creates an empty dataset and adds it to the specified dataset group
create_dataset_group	Creates an empty dataset group
create_dataset_import_job	Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset
create_event_tracker	Creates an event tracker that you use when sending event data to the specified dataset group using the PutEvents API
create_filter	Creates a recommendation filter
create_schema	Creates an Amazon Personalize schema from the specified schema string
create_solution	Creates the configuration for training a model
create_solution_version	Trains or retrains an active solution
delete_campaign	Removes a campaign by deleting the solution deployment
delete_dataset	Deletes a dataset
delete_dataset_group	Deletes a dataset group
delete_event_tracker	Deletes the event tracker
delete_filter	Deletes a filter
delete_schema	Deletes a schema
delete_solution	Deletes all versions of a solution and the Solution object itself
describe_algorithm	Describes the given algorithm
describe_batch_inference_job	Gets the properties of a batch inference job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate the recommendations
describe_campaign	Describes the given campaign, including its status
describe_dataset	Describes the given dataset
describe_dataset_group	Describes the given dataset group
describe_dataset_import_job	Describes the dataset import job created by CreateDatasetImportJob, including the import job status
describe_event_tracker	Describes an event tracker
describe_feature_transformation	Describes the given feature transformation
describe_filter	Describes a filter's properties
describe_recipe	Describes a recipe
describe_schema	Describes a schema
describe_solution	Describes a solution
describe_solution_version	Describes a specific version of a solution
get_solution_metrics	Gets the metrics for the specified solution version
list_batch_inference_jobs	Gets a list of the batch inference jobs that have been performed off of a solution version
list_campaigns	Returns a list of campaigns that use the given solution
list_dataset_groups	Returns a list of dataset groups
list_dataset_import_jobs	Returns a list of dataset import jobs that use the given dataset
list_datasets	Returns the list of datasets contained in the given dataset group
list_event_trackers	Returns the list of event trackers associated with the account
list_filters	Lists all filters that belong to a given dataset group
list_recipes	Returns a list of available recipes
list_schemas	Returns the list of schemas associated with the account
list_solutions	Returns a list of solutions that use the given dataset group
list_solution_versions	Returns a list of solution versions for the given solution
update_campaign	Updates a campaign by either deploying a new solution or changing the value of the campaign's minProvisionedTPS parameter

Examples

if (FALSE) {
svc <- personalize()
svc$create_batch_inference_job(
  Foo = 123
)
}