Crate rusoto_personalize
source · [−]Expand description
Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.
If you’re using the service, you’re probably looking for PersonalizeClient and Personalize.
Structs
Describes a custom algorithm.
Describes an algorithm image.
When the solution performs AutoML (performAutoML
is true in CreateSolution), Amazon Personalize determines which recipe, from the specified list, optimizes the given metric. Amazon Personalize then uses that recipe for the solution.
When the solution performs AutoML (performAutoML
is true in CreateSolution), specifies the recipe that best optimized the specified metric.
Contains information on a batch inference job.
The configuration details of a batch inference job.
The input configuration of a batch inference job.
The output configuration parameters of a batch inference job.
A truncated version of the BatchInferenceJob datatype. The ListBatchInferenceJobs operation returns a list of batch inference job summaries.
Describes a deployed solution version, otherwise known as a campaign. For more information on campaigns, see CreateCampaign.
The configuration details of a campaign.
Provides a summary of the properties of a campaign. For a complete listing, call the DescribeCampaign API.
Provides a summary of the properties of a campaign update. For a complete listing, call the DescribeCampaign API.
Provides the name and range of a categorical hyperparameter.
Provides the name and range of a continuous hyperparameter.
Describes the data source that contains the data to upload to a dataset.
Provides metadata for a dataset.
Describes a job that exports a dataset to an Amazon S3 bucket. For more information, see CreateDatasetExportJob.
A dataset export job can be in one of the following states:
-
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
The output configuration parameters of a dataset export job.
Provides a summary of the properties of a dataset export job. For a complete listing, call the DescribeDatasetExportJob API.
A dataset group is a collection of related datasets (Interactions, User, and Item). You create a dataset group by calling CreateDatasetGroup. You then create a dataset and add it to a dataset group by calling CreateDataset. The dataset group is used to create and train a solution by calling CreateSolution. A dataset group can contain only one of each type of dataset.
You can specify an AWS Key Management Service (KMS) key to encrypt the datasets in the group.
Provides a summary of the properties of a dataset group. For a complete listing, call the DescribeDatasetGroup API.
Describes a job that imports training data from a data source (Amazon S3 bucket) to an Amazon Personalize dataset. For more information, see CreateDatasetImportJob.
A dataset import job can be in one of the following states:
-
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
Provides a summary of the properties of a dataset import job. For a complete listing, call the DescribeDatasetImportJob API.
Describes the schema for a dataset. For more information on schemas, see CreateSchema.
Provides a summary of the properties of a dataset schema. For a complete listing, call the DescribeSchema API.
Provides a summary of the properties of a dataset. For a complete listing, call the DescribeDataset API.
Provides the name and default range of a categorical hyperparameter and whether the hyperparameter is tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).
Provides the name and default range of a continuous hyperparameter and whether the hyperparameter is tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).
Specifies the hyperparameters and their default ranges. Hyperparameters can be categorical, continuous, or integer-valued.
Provides the name and default range of a integer-valued hyperparameter and whether the hyperparameter is tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).
Provides information about an event tracker.
Provides a summary of the properties of an event tracker. For a complete listing, call the DescribeEventTracker API.
Provides feature transformation information. Feature transformation is the process of modifying raw input data into a form more suitable for model training.
Contains information on a recommendation filter, including its ARN, status, and filter expression.
A short summary of a filter's attributes.
Describes the properties for hyperparameter optimization (HPO).
The metric to optimize during hyperparameter optimization (HPO).
Amazon Personalize doesn't support configuring the hpoObjective
at this time.
Describes the resource configuration for hyperparameter optimization (HPO).
Specifies the hyperparameters and their ranges. Hyperparameters can be categorical, continuous, or integer-valued.
Provides the name and range of an integer-valued hyperparameter.
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.
A client for the Amazon Personalize API.
Provides information about a recipe. Each recipe provides an algorithm that Amazon Personalize uses in model training when you use the CreateSolution operation.
Provides a summary of the properties of a recipe. For a complete listing, call the DescribeRecipe API.
The configuration details of an Amazon S3 input or output bucket.
An object that provides information about a solution. A solution is a trained model that can be deployed as a campaign.
Describes the configuration properties for the solution.
Provides a summary of the properties of a solution. For a complete listing, call the DescribeSolution API.
An object that provides information about a specific version of a Solution.
Provides a summary of the properties of a solution version. For a complete listing, call the DescribeSolutionVersion API.
If hyperparameter optimization (HPO) was performed, contains the hyperparameter values of the best performing model.
Enums
Errors returned by CreateBatchInferenceJob
Errors returned by CreateCampaign
Errors returned by CreateDataset
Errors returned by CreateDatasetExportJob
Errors returned by CreateDatasetGroup
Errors returned by CreateDatasetImportJob
Errors returned by CreateEventTracker
Errors returned by CreateFilter
Errors returned by CreateSchema
Errors returned by CreateSolution
Errors returned by CreateSolutionVersion
Errors returned by DeleteCampaign
Errors returned by DeleteDataset
Errors returned by DeleteDatasetGroup
Errors returned by DeleteEventTracker
Errors returned by DeleteFilter
Errors returned by DeleteSchema
Errors returned by DeleteSolution
Errors returned by DescribeAlgorithm
Errors returned by DescribeBatchInferenceJob
Errors returned by DescribeCampaign
Errors returned by DescribeDataset
Errors returned by DescribeDatasetExportJob
Errors returned by DescribeDatasetGroup
Errors returned by DescribeDatasetImportJob
Errors returned by DescribeEventTracker
Errors returned by DescribeFeatureTransformation
Errors returned by DescribeFilter
Errors returned by DescribeRecipe
Errors returned by DescribeSchema
Errors returned by DescribeSolution
Errors returned by DescribeSolutionVersion
Errors returned by GetSolutionMetrics
Errors returned by ListBatchInferenceJobs
Errors returned by ListCampaigns
Errors returned by ListDatasetExportJobs
Errors returned by ListDatasetGroups
Errors returned by ListDatasetImportJobs
Errors returned by ListDatasets
Errors returned by ListEventTrackers
Errors returned by ListFilters
Errors returned by ListRecipes
Errors returned by ListSchemas
Errors returned by ListSolutionVersions
Errors returned by ListSolutions
Errors returned by StopSolutionVersionCreation
Errors returned by UpdateCampaign
Traits
Trait representing the capabilities of the Amazon Personalize API. Amazon Personalize clients implement this trait.