logo
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.