AWS.Personalize (aws-elixir v0.7.0) View Source
Amazon Personalize is a machine learning service that makes it easy to add individualized recommendations to customers.
Link to this section Summary
Functions
Creates a batch inference job.
Creates a campaign by deploying a solution version.
Creates an empty dataset and adds it to the specified dataset group.
Creates an empty dataset group.
Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset.
Creates an event tracker that you use when sending event data to the specified dataset group using the PutEvents API.
Creates a recommendation filter.
Creates an Amazon Personalize schema from the specified schema string.
Creates the configuration for training a model.
Trains or retrains an active solution.
Removes a campaign by deleting the solution deployment.
Deletes a dataset.
Deletes a dataset group.
Deletes the event tracker.
Deletes a filter.
Deletes a schema.
Deletes all versions of a solution and the Solution
object itself.
Describes the given algorithm.
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.
Describes the given campaign, including its status.
Describes the given dataset.
Describes the given dataset group.
Describes the dataset import job created by CreateDatasetImportJob
, including
the import job status.
Describes an event tracker.
Describes the given feature transformation.
Describes a filter's properties.
Describes a recipe.
Describes a schema.
Describes a solution.
Describes a specific version of a solution.
Gets the metrics for the specified solution version.
Gets a list of the batch inference jobs that have been performed off of a solution version.
Returns a list of campaigns that use the given solution.
Returns a list of dataset groups.
Returns a list of dataset import jobs that use the given dataset.
Returns the list of datasets contained in the given dataset group.
Returns the list of event trackers associated with the account.
Lists all filters that belong to a given dataset group.
Returns a list of available recipes.
Returns the list of schemas associated with the account.
Returns a list of solution versions for the given solution.
Returns a list of solutions that use the given dataset group.
Updates a campaign by either deploying a new solution or changing the value of
the campaign's minProvisionedTPS
parameter.
Link to this section Functions
Creates a batch inference job.
The operation can handle up to 50 million records and the input file must be in
JSON format. For more information, see recommendations-batch
.
Creates a campaign by deploying a solution version.
When a client calls the GetRecommendations and GetPersonalizedRanking APIs, a campaign is specified in the request.
Minimum Provisioned TPS and Auto-Scaling
A transaction is a single GetRecommendations
or GetPersonalizedRanking
call.
Transactions per second (TPS) is the throughput and unit of billing for Amazon
Personalize. The minimum provisioned TPS (minProvisionedTPS
) specifies the
baseline throughput provisioned by Amazon Personalize, and thus, the minimum
billing charge. If your TPS increases beyond minProvisionedTPS
, Amazon
Personalize auto-scales the provisioned capacity up and down, but never below
minProvisionedTPS
, to maintain a 70% utilization. There's a short time delay
while the capacity is increased that might cause loss of transactions. It's
recommended to start with a low minProvisionedTPS
, track your usage using
Amazon CloudWatch metrics, and then increase the minProvisionedTPS
as
necessary.
Status
A campaign can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the campaign status, call DescribeCampaign
.
Wait until the status
of the campaign is ACTIVE
before asking the campaign
for recommendations.
Related APIs
ListCampaigns
DescribeCampaign
UpdateCampaign
DeleteCampaign
Creates an empty dataset and adds it to the specified dataset group.
Use CreateDatasetImportJob
to import your training data to a dataset.
There are three types of datasets:
Interactions
Items
Users
Each dataset type has an associated schema with required field types. Only the
Interactions
dataset is required in order to train a model (also referred to
as creating a solution).
A dataset can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the status of the dataset, call DescribeDataset
.
Related APIs
CreateDatasetGroup
ListDatasets
DescribeDataset
DeleteDataset
Creates an empty dataset group.
A dataset group contains related datasets that supply data for training a model. A dataset group can contain at most three datasets, one for each type of dataset:
Interactions
Items
Users
To train a model (create a solution), a dataset group that contains an
Interactions
dataset is required. Call CreateDataset
to add a dataset to the
group.
A dataset group can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING
To get the status of the dataset group, call DescribeDatasetGroup
. If the
status shows as CREATE FAILED, the response includes a failureReason
key,
which describes why the creation failed.
You must wait until the status
of the dataset group is ACTIVE
before adding
a dataset to the group.
You can specify an AWS Key Management Service (KMS) key to encrypt the datasets in the group. If you specify a KMS key, you must also include an AWS Identity and Access Management (IAM) role that has permission to access the key.
APIs that require a dataset group ARN in the request
CreateDataset
CreateEventTracker
CreateSolution
Related APIs
ListDatasetGroups
DescribeDatasetGroup
DeleteDatasetGroup
Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset.
To allow Amazon Personalize to import the training data, you must specify an AWS Identity and Access Management (IAM) role that has permission to read from the data source, as Amazon Personalize makes a copy of your data and processes it in an internal AWS system.
The dataset import job replaces any previous data in the dataset.
Status
A dataset import job can be in one of the following states:
- CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
To get the status of the import job, call DescribeDatasetImportJob
, providing
the Amazon Resource Name (ARN) of the dataset import job. The dataset import is
complete when the status shows as ACTIVE. If the status shows as CREATE FAILED,
the response includes a failureReason
key, which describes why the job failed.
Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset.
Related APIs
ListDatasetImportJobs
DescribeDatasetImportJob
Creates an event tracker that you use when sending event data to the specified dataset group using the PutEvents API.
When Amazon Personalize creates an event tracker, it also creates an
event-interactions dataset in the dataset group associated with the event
tracker. The event-interactions dataset stores the event data from the
PutEvents
call. The contents of this dataset are not available to the user.
Only one event tracker can be associated with a dataset group. You will get an
error if you call CreateEventTracker
using the same dataset group as an
existing event tracker.
When you send event data you include your tracking ID. The tracking ID identifies the customer and authorizes the customer to send the data.
The event tracker can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the status of the event tracker, call DescribeEventTracker
.
The event tracker must be in the ACTIVE state before using the tracking ID.
Related APIs
ListEventTrackers
DescribeEventTracker
DeleteEventTracker
Creates a recommendation filter.
For more information, see Using Filters with Amazon Personalize.
Creates an Amazon Personalize schema from the specified schema string.
The schema you create must be in Avro JSON format.
Amazon Personalize recognizes three schema variants. Each schema is associated
with a dataset type and has a set of required field and keywords. You specify a
schema when you call CreateDataset
.
Related APIs
ListSchemas
DescribeSchema
DeleteSchema
Creates the configuration for training a model.
A trained model is known as a solution. After the configuration is created, you
train the model (create a solution) by calling the CreateSolutionVersion
operation. Every time you call CreateSolutionVersion
, a new version of the
solution is created.
After creating a solution version, you check its accuracy by calling
GetSolutionMetrics
. When you are satisfied with the version, you deploy it
using CreateCampaign
. The campaign provides recommendations to a client
through the
GetRecommendations
API.
To train a model, Amazon Personalize requires training data and a recipe. The
training data comes from the dataset group that you provide in the request. A
recipe specifies the training algorithm and a feature transformation. You can
specify one of the predefined recipes provided by Amazon Personalize.
Alternatively, you can specify performAutoML
and Amazon Personalize will
analyze your data and select the optimum USER_PERSONALIZATION recipe for you.
Status
A solution can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
To get the status of the solution, call DescribeSolution
. Wait until the
status shows as ACTIVE before calling CreateSolutionVersion
.
Related APIs
ListSolutions
CreateSolutionVersion
DescribeSolution
DeleteSolution
ListSolutionVersions
DescribeSolutionVersion
Trains or retrains an active solution.
A solution is created using the CreateSolution
operation and must be in the
ACTIVE state before calling CreateSolutionVersion
. A new version of the
solution is created every time you call this operation.
Status
A solution version can be in one of the following states:
- CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
To get the status of the version, call DescribeSolutionVersion
. Wait until the
status shows as ACTIVE before calling CreateCampaign
.
If the status shows as CREATE FAILED, the response includes a failureReason
key, which describes why the job failed.
Related APIs
ListSolutionVersions
DescribeSolutionVersion
ListSolutions
CreateSolution
DescribeSolution
DeleteSolution
Removes a campaign by deleting the solution deployment.
The solution that the campaign is based on is not deleted and can be redeployed
when needed. A deleted campaign can no longer be specified in a
GetRecommendations
request. For more information on campaigns, see CreateCampaign
.
Deletes a dataset.
You can't delete a dataset if an associated DatasetImportJob
or
SolutionVersion
is in the CREATE PENDING or IN PROGRESS state. For more
information on datasets, see CreateDataset
.
Deletes a dataset group.
Before you delete a dataset group, you must delete the following:
All associated event trackers.
All associated solutions.
All datasets in the dataset group.
Deletes the event tracker.
Does not delete the event-interactions dataset from the associated dataset
group. For more information on event trackers, see CreateEventTracker
.
Deletes a filter.
Deletes a schema.
Before deleting a schema, you must delete all datasets referencing the schema.
For more information on schemas, see CreateSchema
.
Deletes all versions of a solution and the Solution
object itself.
Before deleting a solution, you must delete all campaigns based on the solution.
To determine what campaigns are using the solution, call ListCampaigns
and
supply the Amazon Resource Name (ARN) of the solution. You can't delete a
solution if an associated SolutionVersion
is in the CREATE PENDING or IN
PROGRESS state. For more information on solutions, see CreateSolution
.
Describes the given algorithm.
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.
Describes the given campaign, including its status.
A campaign can be in one of the following states:
CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
DELETE PENDING > DELETE IN_PROGRESS
When the status
is CREATE FAILED
, the response includes the failureReason
key, which describes why.
For more information on campaigns, see CreateCampaign
.
Describes the given dataset.
For more information on datasets, see CreateDataset
.
Describes the given dataset group.
For more information on dataset groups, see CreateDatasetGroup
.
Describes the dataset import job created by CreateDatasetImportJob
, including
the import job status.
Describes an event tracker.
The response includes the trackingId
and status
of the event tracker. For
more information on event trackers, see CreateEventTracker
.
Describes the given feature transformation.
Describes a filter's properties.
Describes a recipe.
A recipe contains three items:
An algorithm that trains a model.
Hyperparameters that govern the training.
Feature transformation information for modifying the input data before training.
Amazon Personalize provides a set of predefined recipes. You specify a recipe
when you create a solution with the CreateSolution
API. CreateSolution
trains a model by using the algorithm in the specified recipe and a training
dataset. The solution, when deployed as a campaign, can provide recommendations
using the
GetRecommendations
API.
Describes a schema.
For more information on schemas, see CreateSchema
.
Describes a solution.
For more information on solutions, see CreateSolution
.
Describes a specific version of a solution.
For more information on solutions, see CreateSolution
.
Gets the metrics for the specified solution version.
Gets a list of the batch inference jobs that have been performed off of a solution version.
Returns a list of campaigns that use the given solution.
When a solution is not specified, all the campaigns associated with the account
are listed. The response provides the properties for each campaign, including
the Amazon Resource Name (ARN). For more information on campaigns, see
CreateCampaign
.
Returns a list of dataset groups.
The response provides the properties for each dataset group, including the
Amazon Resource Name (ARN). For more information on dataset groups, see
CreateDatasetGroup
.
Returns a list of dataset import jobs that use the given dataset.
When a dataset is not specified, all the dataset import jobs associated with the
account are listed. The response provides the properties for each dataset import
job, including the Amazon Resource Name (ARN). For more information on dataset
import jobs, see CreateDatasetImportJob
. For more information on datasets, see
CreateDataset
.
Returns the list of datasets contained in the given dataset group.
The response provides the properties for each dataset, including the Amazon
Resource Name (ARN). For more information on datasets, see CreateDataset
.
Returns the list of event trackers associated with the account.
The response provides the properties for each event tracker, including the
Amazon Resource Name (ARN) and tracking ID. For more information on event
trackers, see CreateEventTracker
.
Lists all filters that belong to a given dataset group.
Returns a list of available recipes.
The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).
Returns the list of schemas associated with the account.
The response provides the properties for each schema, including the Amazon
Resource Name (ARN). For more information on schemas, see CreateSchema
.
Returns a list of solution versions for the given solution.
When a solution is not specified, all the solution versions associated with the
account are listed. The response provides the properties for each solution
version, including the Amazon Resource Name (ARN). For more information on
solutions, see CreateSolution
.
Returns a list of solutions that use the given dataset group.
When a dataset group is not specified, all the solutions associated with the
account are listed. The response provides the properties for each solution,
including the Amazon Resource Name (ARN). For more information on solutions, see
CreateSolution
.
Updates a campaign by either deploying a new solution or changing the value of
the campaign's minProvisionedTPS
parameter.
To update a campaign, the campaign status must be ACTIVE or CREATE FAILED. Check
the campaign status using the DescribeCampaign
API.
You must wait until the status
of the updated campaign is ACTIVE
before
asking the campaign for recommendations.
For more information on campaigns, see CreateCampaign
.