paws.machine.learning package

bedrock

Amazon Bedrock

augmentedairuntime

Amazon Augmented AI Runtime

augmentedairuntime_delete_human_loop

Deletes the specified human loop for a flow definition

augmentedairuntime_list_human_loops

Returns information about human loops, given the specified parameters

augmentedairuntime_describe_human_loop

Returns information about the specified human loop

augmentedairuntime_stop_human_loop

Stops the specified human loop

augmentedairuntime_start_human_loop

Starts a human loop, provided that at least one activation condition is met

bedrock_create_evaluation_job

Creates an evaluation job

bedrock_batch_delete_evaluation_job

Deletes a batch of evaluation jobs

bedrock_create_guardrail

Creates a guardrail to block topics and to implement safeguards for your generative AI applications

bedrock_create_guardrail_version

Creates a version of the guardrail

bedrock_create_model_import_job

Creates a model import job to import model that you have customized in other environments, such as Amazon SageMaker

bedrock_create_marketplace_model_endpoint

Creates an endpoint for a model from Amazon Bedrock Marketplace

bedrock_create_model_invocation_job

Creates a batch inference job to invoke a model on multiple prompts

bedrock_create_model_customization_job

Creates a fine-tuning job to customize a base model

bedrock_delete_inference_profile

Deletes an application inference profile

bedrock_delete_guardrail

Deletes a guardrail

bedrock_create_provisioned_model_throughput

Creates dedicated throughput for a base or custom model with the model units and for the duration that you specify

bedrock_delete_custom_model

Deletes a custom model that you created earlier

bedrock_create_model_copy_job

Copies a model to another region so that it can be used there

bedrock_get_imported_model

Gets properties associated with a customized model you imported

bedrock_get_inference_profile

Gets information about an inference profile

bedrock_delete_imported_model

Deletes a custom model that you imported earlier

bedrock_create_inference_profile

Creates an application inference profile to track metrics and costs when invoking a model

bedrock_get_model_copy_job

Retrieves information about a model copy job

bedrock_deregister_marketplace_model_endpoint

Deregisters an endpoint for a model from Amazon Bedrock Marketplace

bedrock_list_model_import_jobs

Returns a list of import jobs you've submitted

bedrock_get_marketplace_model_endpoint

Retrieves details about a specific endpoint for a model from Amazon Bedrock Marketplace

bedrock_delete_provisioned_model_throughput

Deletes a Provisioned Throughput

bedrock_list_provisioned_model_throughputs

Lists the Provisioned Throughputs in the account

bedrock_list_custom_models

Returns a list of the custom models that you have created with the CreateModelCustomizationJob operation

bedrock_list_model_customization_jobs

Returns a list of model customization jobs that you have submitted

bedrock_delete_marketplace_model_endpoint

Deletes an endpoint for a model from Amazon Bedrock Marketplace

bedrock_tag_resource

Associate tags with a resource

bedrock_list_evaluation_jobs

Lists all existing evaluation jobs

bedrock_stop_model_invocation_job

Stops a batch inference job

bedrock_list_inference_profiles

Returns a list of inference profiles that you can use

bedrock_list_imported_models

Returns a list of models you've imported

bedrock_delete_model_invocation_logging_configuration

Delete the invocation logging

bedrock_get_model_invocation_logging_configuration

Get the current configuration values for model invocation logging

bedrock_get_guardrail

Gets details about a guardrail

bedrock_get_foundation_model

Get details about a Amazon Bedrock foundation model

bedrock_list_model_invocation_jobs

Lists all batch inference jobs in the account

bedrock_get_custom_model

Get the properties associated with a Amazon Bedrock custom model that you have created

bedrock_get_model_invocation_job

Gets details about a batch inference job

bedrock_get_evaluation_job

Gets information about an evaluation job, such as the status of the job

bedrock_list_prompt_routers

Retrieves a list of prompt routers

bedrock_get_prompt_router

Retrieves details about a prompt router

bedrock_get_provisioned_model_throughput

Returns details for a Provisioned Throughput

bedrockagent_create_flow

Creates a prompt flow that you can use to send an input through various steps to yield an output

bedrock_list_guardrails

Lists details about all the guardrails in an account

bedrockagent

Agents for Amazon Bedrock

bedrockagent_associate_agent_collaborator

Makes an agent a collaborator for another agent

bedrock_list_foundation_models

Lists Amazon Bedrock foundation models that you can use

bedrockagent_create_flow_version

Creates a version of the flow that you can deploy

bedrock_list_marketplace_model_endpoints

Lists the endpoints for models from Amazon Bedrock Marketplace in your Amazon Web Services account

bedrockagent_create_flow_alias

Creates an alias of a flow for deployment

bedrock_update_marketplace_model_endpoint

Updates the configuration of an existing endpoint for a model from Amazon Bedrock Marketplace

bedrockagent_associate_agent_knowledge_base

Associates a knowledge base with an agent

bedrock_register_marketplace_model_endpoint

Registers an existing Amazon SageMaker endpoint with Amazon Bedrock Marketplace, allowing it to be used with Amazon Bedrock APIs

bedrock_list_tags_for_resource

List the tags associated with the specified resource

bedrock_put_model_invocation_logging_configuration

Set the configuration values for model invocation logging

bedrock_list_model_copy_jobs

Returns a list of model copy jobs that you have submitted

bedrock_update_provisioned_model_throughput

Updates the name or associated model for a Provisioned Throughput

bedrockagent_create_data_source

Connects a knowledge base to a data source

bedrockagent_create_prompt_version

Creates a static snapshot of your prompt that can be deployed to production

bedrockagent_get_flow_alias

Retrieves information about a flow

bedrock_stop_evaluation_job

Stops an evaluation job that is current being created or running

bedrock_stop_model_customization_job

Stops an active model customization job

bedrockagent_delete_prompt

Deletes a prompt or a version of it, depending on whether you include the promptVersion field or not

bedrockagent_delete_agent

Deletes an agent

bedrockagent_get_flow_version

Retrieves information about a version of a flow

bedrockagent_delete_knowledge_base_documents

Deletes documents from a data source and syncs the changes to the knowledge base that is connected to it

bedrockagent_get_knowledge_base_documents

Retrieves specific documents from a data source that is connected to a knowledge base

bedrockagent_get_data_source

Gets information about a data source

bedrockagent_delete_flow_version

Deletes a version of a flow

bedrockagent_get_agent_action_group

Gets information about an action group for an agent

bedrockagent_list_flow_versions

Returns a list of information about each flow

bedrockagent_list_tags_for_resource

List all the tags for the resource you specify

bedrockagent_list_flow_aliases

Returns a list of aliases for a flow

bedrockagent_list_prompts

Returns either information about the working draft (DRAFT version) of each prompt in an account, or information about of all versions of a prompt, depending on whether you include the promptIdentifier field or not

bedrockagent_get_agent

Gets information about an agent

bedrockagent_get_prompt

Retrieves information about the working draft (DRAFT version) of a prompt or a version of it, depending on whether you include the promptVersion field or not

bedrockagent_delete_flow

Deletes a flow

bedrockagent_delete_agent_action_group

Deletes an action group in an agent

bedrock_untag_resource

Remove one or more tags from a resource

bedrockagent_create_agent

Creates an agent that orchestrates interactions between foundation models, data sources, software applications, user conversations, and APIs to carry out tasks to help customers

bedrock_update_guardrail

Updates a guardrail with the values you specify

bedrockagent_delete_agent_alias

Deletes an alias of an agent

bedrockagent_list_flows

Returns a list of flows and information about each flow

bedrockagent_delete_knowledge_base

Deletes a knowledge base

bedrockagent_delete_flow_alias

Deletes an alias of a flow

bedrockagent_update_agent_alias

Updates configurations for an alias of an agent

bedrockagent_update_agent_collaborator

Updates an agent's collaborator

bedrockagent_disassociate_agent_collaborator

Disassociates an agent collaborator

bedrockagent_update_agent

Updates the configuration of an agent

bedrockagent_update_agent_action_group

Updates the configuration for an action group for an agent

bedrock_get_model_customization_job

Retrieves the properties associated with a model-customization job, including the status of the job

bedrockagent_get_knowledge_base

Gets information about a knoweldge base

bedrockagent_get_flow

Retrieves information about a flow

bedrockagent_get_ingestion_job

Gets information about a data ingestion job

bedrockagent_get_agent_collaborator

Retrieves information about an agent's collaborator

bedrockagent_prepare_flow

Prepares the DRAFT version of a flow so that it can be invoked

bedrockagent_ingest_knowledge_base_documents

Ingests documents directly into the knowledge base that is connected to the data source

bedrockagent_get_agent_alias

Gets information about an alias of an agent

bedrockagent_disassociate_agent_knowledge_base

Disassociates a knowledge base from an agent

bedrockagent_list_agent_aliases

Lists the aliases of an agent and information about each one

bedrockagentruntime_optimize_prompt

Optimizes a prompt for the task that you specify

bedrockagent_update_prompt

Modifies a prompt in your prompt library

bedrockagent_update_knowledge_base

Updates the configuration of a knowledge base with the fields that you specify

bedrockagent_list_agent_action_groups

Lists the action groups for an agent and information about each one

bedrockagentruntime_rerank

Reranks the relevance of sources based on queries

bedrock_get_model_import_job

Retrieves the properties associated with import model job, including the status of the job

bedrockagent_create_agent_alias

Creates an alias of an agent that can be used to deploy the agent

bedrockagent_prepare_agent

Creates a DRAFT version of the agent that can be used for internal testing

bedrockagent_list_agents

Lists the agents belonging to an account and information about each agent

bedrockagent_create_agent_action_group

Creates an action group for an agent

bedrockagent_create_prompt

Creates a prompt in your prompt library that you can add to a flow

bedrockdataautomation_list_data_automation_projects

Lists all existing Amazon Bedrock Data Automation Projects

bedrockagent_delete_agent_version

Deletes a version of an agent

bedrockagent_list_agent_collaborators

Retrieve a list of an agent's collaborators

bedrockagent_list_data_sources

Lists the data sources in a knowledge base and information about each one

bedrockagentruntime_delete_agent_memory

Deletes memory from the specified memory identifier

bedrockagent_update_flow_alias

Modifies the alias of a flow

bedrockagent_delete_data_source

Deletes a data source from a knowledge base

bedrockagent_create_knowledge_base

Creates a knowledge base

bedrockagent_get_agent_knowledge_base

Gets information about a knowledge base associated with an agent

bedrockagent_get_agent_version

Gets details about a version of an agent

bedrockagent_update_agent_knowledge_base

Updates the configuration for a knowledge base that has been associated with an agent

bedrockdataautomation_delete_data_automation_project

Deletes an existing Amazon Bedrock Data Automation Project

bedrockagent_update_data_source

Updates the configurations for a data source connector

bedrockruntime

Amazon Bedrock Runtime

bedrockdataautomation_get_blueprint

Gets an existing Amazon Bedrock Data Automation Blueprint

bedrockagentruntime_generate_query

Generates an SQL query from a natural language query

bedrockagent_list_knowledge_base_documents

Retrieves all the documents contained in a data source that is connected to a knowledge base

bedrockagent_list_knowledge_bases

Lists the knowledge bases in an account

bedrockagent_tag_resource

Associate tags with a resource

bedrockagentruntime_get_agent_memory

Gets the sessions stored in the memory of the agent

bedrockagent_list_agent_versions

Lists the versions of an agent and information about each version

bedrockagent_list_agent_knowledge_bases

Lists knowledge bases associated with an agent and information about each one

bedrockagentruntime_retrieve_and_generate

Queries a knowledge base and generates responses based on the retrieved results and using the specified foundation model or inference profile

bedrockagent_update_flow

Modifies a flow

bedrockagentruntime_retrieve

Queries a knowledge base and retrieves information from it

bedrockagent_untag_resource

Remove tags from a resource

bedrockdataautomationruntime_invoke_data_automation_async

Async API: Invoke data automation

bedrockdataautomation_update_blueprint

Updates an existing Amazon Bedrock Data Automation Blueprint

bedrockagent_validate_flow_definition

Validates the definition of a flow

bedrockagentruntime_invoke_agent

Sends a prompt for the agent to process and respond to

bedrockdataautomationruntime_get_data_automation_status

API used to get data automation status

comprehend_batch_detect_entities

Inspects the text of a batch of documents for named entities and returns information about them

comprehend_batch_detect_dominant_language

Determines the dominant language of the input text for a batch of documents

bedrockdataautomationruntime

Runtime for Amazon Bedrock Data Automation

bedrockruntime_apply_guardrail

The action to apply a guardrail

bedrockdataautomation_get_data_automation_project

Gets an existing Amazon Bedrock Data Automation Project

bedrockdataautomation_list_blueprints

Lists all existing Amazon Bedrock Data Automation Blueprints

bedrockdataautomation_update_data_automation_project

Updates an existing Amazon Bedrock Data Automation Project

bedrockagentruntime

Agents for Amazon Bedrock Runtime

comprehend_create_document_classifier

Creates a new document classifier that you can use to categorize documents

comprehend_create_dataset

Creates a dataset to upload training or test data for a model associated with a flywheel

comprehend_batch_detect_syntax

Inspects the text of a batch of documents for the syntax and part of speech of the words in the document and returns information about them

comprehend_describe_entity_recognizer

Provides details about an entity recognizer including status, S3 buckets containing training data, recognizer metadata, metrics, and so on

bedrockdataautomation

Data Automation for Amazon Bedrock

comprehend_delete_resource_policy

Deletes a resource-based policy that is attached to a custom model

bedrockruntime_get_async_invoke

Retrieve information about an asynchronous invocation

comprehend_describe_events_detection_job

Gets the status and details of an events detection job

comprehend_batch_detect_key_phrases

Detects the key noun phrases found in a batch of documents

comprehend_batch_detect_targeted_sentiment

Inspects a batch of documents and returns a sentiment analysis for each entity identified in the documents

bedrockdataautomation_create_blueprint_version

Creates a new version of an existing Amazon Bedrock Data Automation Blueprint

comprehend_batch_detect_sentiment

Inspects a batch of documents and returns an inference of the prevailing sentiment, POSITIVE, NEUTRAL, MIXED, or NEGATIVE, in each one

comprehend_describe_targeted_sentiment_detection_job

Gets the properties associated with a targeted sentiment detection job

comprehend_delete_endpoint

Deletes a model-specific endpoint for a previously-trained custom model

comprehend_describe_dataset

Returns information about the dataset that you specify

bedrockdataautomation_create_blueprint

Creates an Amazon Bedrock Data Automation Blueprint

bedrockruntime_invoke_model

Invokes the specified Amazon Bedrock model to run inference using the prompt and inference parameters provided in the request body

comprehend_create_endpoint

Creates a model-specific endpoint for synchronous inference for a previously trained custom model For information about endpoints, see Managing endpoints

bedrockruntime_invoke_model_with_response_stream

Invoke the specified Amazon Bedrock model to run inference using the prompt and inference parameters provided in the request body

bedrockagentruntime_retrieve_and_generate_stream

Queries a knowledge base and generates responses based on the retrieved results, with output in streaming format

comprehend_describe_endpoint

Gets the properties associated with a specific endpoint

comprehend_delete_entity_recognizer

Deletes an entity recognizer

bedrockagent_list_ingestion_jobs

Lists the data ingestion jobs for a data source

comprehend_create_entity_recognizer

Creates an entity recognizer using submitted files

comprehend_describe_document_classification_job

Gets the properties associated with a document classification job

comprehend_describe_flywheel

Provides configuration information about the flywheel

comprehend_delete_document_classifier

Deletes a previously created document classifier

bedrockruntime_list_async_invokes

Lists asynchronous invocations

comprehend_create_flywheel

A flywheel is an Amazon Web Services resource that orchestrates the ongoing training of a model for custom classification or custom entity recognition

comprehend_describe_document_classifier

Gets the properties associated with a document classifier

comprehend_describe_flywheel_iteration

Retrieve the configuration properties of a flywheel iteration

comprehend_describe_entities_detection_job

Gets the properties associated with an entities detection job

comprehend_list_document_classification_jobs

Gets a list of the documentation classification jobs that you have submitted

comprehend_describe_topics_detection_job

Gets the properties associated with a topic detection job

comprehend_list_document_classifier_summaries

Gets a list of summaries of the document classifiers that you have created

comprehend_list_datasets

List the datasets that you have configured in this Region

comprehend_import_model

Creates a new custom model that replicates a source custom model that you import

comprehend_list_flywheel_iteration_history

Information about the history of a flywheel iteration

comprehend_detect_targeted_sentiment

Inspects the input text and returns a sentiment analysis for each entity identified in the text

comprehend_detect_sentiment

Inspects text and returns an inference of the prevailing sentiment (POSITIVE, NEUTRAL, MIXED, or NEGATIVE)

comprehend_detect_syntax

Inspects text for syntax and the part of speech of words in the document

comprehend_describe_sentiment_detection_job

Gets the properties associated with a sentiment detection job

comprehend_describe_resource_policy

Gets the details of a resource-based policy that is attached to a custom model, including the JSON body of the policy

comprehend_list_document_classifiers

Gets a list of the document classifiers that you have created

comprehend_list_events_detection_jobs

Gets a list of the events detection jobs that you have submitted

comprehend_list_dominant_language_detection_jobs

Gets a list of the dominant language detection jobs that you have submitted

comprehend_detect_toxic_content

Performs toxicity analysis on the list of text strings that you provide as input

comprehend_list_flywheels

Gets a list of the flywheels that you have created

comprehend_list_key_phrases_detection_jobs

Get a list of key phrase detection jobs that you have submitted

comprehend_list_pii_entities_detection_jobs

Gets a list of the PII entity detection jobs that you have submitted

comprehend_start_document_classification_job

Starts an asynchronous document classification job using a custom classification model

comprehend_describe_dominant_language_detection_job

Gets the properties associated with a dominant language detection job

comprehend_start_dominant_language_detection_job

Starts an asynchronous dominant language detection job for a collection of documents

comprehend_list_sentiment_detection_jobs

Gets a list of sentiment detection jobs that you have submitted

comprehend_stop_events_detection_job

Stops an events detection job in progress

comprehend_start_flywheel_iteration

Start the flywheel iteration

comprehend_start_key_phrases_detection_job

Starts an asynchronous key phrase detection job for a collection of documents

bedrockdataautomation_create_data_automation_project

Creates an Amazon Bedrock Data Automation Project

comprehend_start_topics_detection_job

Starts an asynchronous topic detection job

comprehend_start_targeted_sentiment_detection_job

Starts an asynchronous targeted sentiment detection job for a collection of documents

bedrockagent_stop_ingestion_job

Stops a currently running data ingestion job

bedrockagent_start_ingestion_job

Begins a data ingestion job

bedrockagentruntime_invoke_flow

Invokes an alias of a flow to run the inputs that you specify and return the output of each node as a stream

comprehend_stop_training_entity_recognizer

Stops an entity recognizer training job while in progress

comprehend_stop_pii_entities_detection_job

Stops a PII entities detection job in progress

comprehend_stop_sentiment_detection_job

Stops a sentiment detection job in progress

comprehend_list_tags_for_resource

Lists all tags associated with a given Amazon Comprehend resource

comprehend_start_pii_entities_detection_job

Starts an asynchronous PII entity detection job for a collection of documents

comprehend_list_targeted_sentiment_detection_jobs

Gets a list of targeted sentiment detection jobs that you have submitted

comprehendmedical_describe_icd10cm_inference_job

Gets the properties associated with an InferICD10CM job

comprehendmedical_describe_entities_detection_v2_job

Gets the properties associated with a medical entities detection job

comprehend_tag_resource

Associates a specific tag with an Amazon Comprehend resource

bedrockagentruntime_invoke_inline_agent

Invokes an inline Amazon Bedrock agent using the configurations you provide with the request

bedrockdataautomation_delete_blueprint

Deletes an existing Amazon Bedrock Data Automation Blueprint

comprehendmedical_infer_rx_norm

InferRxNorm detects medications as entities listed in a patient record and links to the normalized concept identifiers in the RxNorm database from the National Library of Medicine

comprehendmedical_infer_icd10cm

InferICD10CM detects medical conditions as entities listed in a patient record and links those entities to normalized concept identifiers in the ICD-10-CM knowledge base from the Centers for Disease Control

comprehend_list_entities_detection_jobs

Gets a list of the entity detection jobs that you have submitted

comprehend_stop_entities_detection_job

Stops an entities detection job in progress

comprehend_list_endpoints

Gets a list of all existing endpoints that you've created

comprehend_list_topics_detection_jobs

Gets a list of the topic detection jobs that you have submitted

comprehend_describe_key_phrases_detection_job

Gets the properties associated with a key phrases detection job

comprehend_describe_pii_entities_detection_job

Gets the properties associated with a PII entities detection job

comprehend_untag_resource

Removes a specific tag associated with an Amazon Comprehend resource

comprehend_stop_key_phrases_detection_job

Stops a key phrases detection job in progress

comprehend_stop_dominant_language_detection_job

Stops a dominant language detection job in progress

comprehend_update_endpoint

Updates information about the specified endpoint

comprehend_put_resource_policy

Attaches a resource-based policy to a custom model

comprehendmedical_start_icd10cm_inference_job

Starts an asynchronous job to detect medical conditions and link them to the ICD-10-CM ontology

comprehendmedical_start_entities_detection_v2_job

Starts an asynchronous medical entity detection job for a collection of documents

comprehendmedical_describe_phi_detection_job

Gets the properties associated with a protected health information (PHI) detection job

forecastqueryservice_query_what_if_forecast

Retrieves a what-if forecast

forecastservice

Amazon Forecast Service

comprehendmedical_list_phi_detection_jobs

Gets a list of protected health information (PHI) detection jobs you have submitted

comprehendmedical_stop_snomedct_inference_job

Stops an InferSNOMEDCT inference job in progress

comprehendmedical_list_icd10cm_inference_jobs

Gets a list of InferICD10CM jobs that you have submitted

comprehendmedical_list_rx_norm_inference_jobs

Gets a list of InferRxNorm jobs that you have submitted

comprehendmedical_stop_rx_norm_inference_job

Stops an InferRxNorm inference job in progress

comprehendmedical_list_snomedct_inference_jobs

Gets a list of InferSNOMEDCT jobs a user has submitted

forecastqueryservice

Amazon Forecast Query Service

comprehendmedical_describe_rx_norm_inference_job

Gets the properties associated with an InferRxNorm job

forecastqueryservice_query_forecast

Retrieves a forecast for a single item, filtered by the supplied criteria

forecastservice_create_monitor

Creates a predictor monitor resource for an existing auto predictor

forecastservice_create_predictor

This operation creates a legacy predictor that does not include all the predictor functionalities provided by Amazon Forecast

forecastservice_create_dataset_group

Creates a dataset group, which holds a collection of related datasets

forecastservice_create_forecast

Creates a forecast for each item in the TARGET_TIME_SERIES dataset that was used to train the predictor

comprehend_delete_flywheel

Deletes a flywheel

forecastservice_create_forecast_export_job

Exports a forecast created by the CreateForecast operation to your Amazon Simple Storage Service (Amazon S3) bucket

bedrockruntime_start_async_invoke

Starts an asynchronous invocation

forecastservice_create_dataset_import_job

Imports your training data to an Amazon Forecast dataset

comprehend_stop_targeted_sentiment_detection_job

Stops a targeted sentiment detection job in progress

comprehend_start_sentiment_detection_job

Starts an asynchronous sentiment detection job for a collection of documents

comprehendmedical_start_snomedct_inference_job

Starts an asynchronous job to detect medical concepts and link them to the SNOMED-CT ontology

forecastservice_create_dataset

Creates an Amazon Forecast dataset

comprehend_stop_training_document_classifier

Stops a document classifier training job while in progress

comprehendmedical_describe_snomedct_inference_job

Gets the properties associated with an InferSNOMEDCT job

forecastservice_delete_dataset

Deletes an Amazon Forecast dataset that was created using the CreateDataset operation

forecastservice_create_predictor_backtest_export_job

Exports backtest forecasts and accuracy metrics generated by the CreateAutoPredictor or CreatePredictor operations

bedrockruntime_converse_stream

Sends messages to the specified Amazon Bedrock model and returns the response in a stream

forecastservice_delete_dataset_group

Deletes a dataset group created using the CreateDatasetGroup operation

bedrockruntime_converse

Sends messages to the specified Amazon Bedrock model

comprehend_detect_entities

Detects named entities in input text when you use the pre-trained model

comprehendmedical_detect_entities

The DetectEntities operation is deprecated

forecastservice_create_explainability

Explainability is only available for Forecasts and Predictors generated from an AutoPredictor (CreateAutoPredictor)

forecastservice_describe_predictor_backtest_export_job

Describes a predictor backtest export job created using the CreatePredictorBacktestExportJob operation

comprehendmedical_list_entities_detection_v2_jobs

Gets a list of medical entity detection jobs that you have submitted

comprehendmedical_stop_entities_detection_v2_job

Stops a medical entities detection job in progress

forecastservice_delete_dataset_import_job

Deletes a dataset import job created using the CreateDatasetImportJob operation

comprehendmedical_infer_snomedct

InferSNOMEDCT detects possible medical concepts as entities and links them to codes from the Systematized Nomenclature of Medicine, Clinical Terms (SNOMED-CT) ontology

forecastservice_list_datasets

Returns a list of datasets created using the CreateDataset operation

forecastservice_list_dataset_import_jobs

Returns a list of dataset import jobs created using the CreateDatasetImportJob operation

forecastservice_describe_what_if_analysis

Describes the what-if analysis created using the CreateWhatIfAnalysis operation

forecastservice_describe_monitor

Describes a monitor resource

forecastservice_create_auto_predictor

Creates an Amazon Forecast predictor

comprehend

Amazon Comprehend

forecastservice_create_explainability_export

Exports an Explainability resource created by the CreateExplainability operation

comprehend_detect_key_phrases

Detects the key noun phrases found in the text

comprehend_classify_document

Creates a classification request to analyze a single document in real-time

comprehend_detect_dominant_language

Determines the dominant language of the input text

forecastservice_delete_explainability

Deletes an Explainability resource

comprehend_contains_pii_entities

Analyzes input text for the presence of personally identifiable information (PII) and returns the labels of identified PII entity types such as name, address, bank account number, or phone number

forecastservice_describe_explainability_export

Describes an Explainability export created using the CreateExplainabilityExport operation

comprehendmedical_stop_icd10cm_inference_job

Stops an InferICD10CM inference job in progress

forecastservice_delete_predictor

Deletes a predictor created using the DescribePredictor or CreatePredictor operations

comprehend_update_flywheel

Update the configuration information for an existing flywheel

forecastservice_resume_resource

Resumes a stopped monitor resource

comprehendmedical

AWS Comprehend Medical

forecastservice_describe_dataset_group

Describes a dataset group created using the CreateDatasetGroup operation

frauddetector_create_batch_import_job

Creates a batch import job

comprehend_detect_pii_entities

Inspects the input text for entities that contain personally identifiable information (PII) and returns information about them

frauddetector_create_batch_prediction_job

Creates a batch prediction job

forecastservice_stop_resource

Stops a resource

forecastservice_create_what_if_analysis

What-if analysis is a scenario modeling technique where you make a hypothetical change to a time series and compare the forecasts generated by these changes against the baseline, unchanged time series

forecastservice_describe_forecast

Describes a forecast created using the CreateForecast operation

forecastservice_delete_explainability_export

Deletes an Explainability export

forecastservice_delete_what_if_forecast

Deletes a what-if forecast created using the CreateWhatIfForecast operation

forecastservice_delete_what_if_forecast_export

Deletes a what-if forecast export created using the CreateWhatIfForecastExport operation

forecastservice_list_tags_for_resource

Lists the tags for an Amazon Forecast resource

forecastservice_describe_forecast_export_job

Describes a forecast export job created using the CreateForecastExportJob operation

frauddetector

Amazon Fraud Detector

forecastservice_list_forecast_export_jobs

Returns a list of forecast export jobs created using the CreateForecastExportJob operation

forecastservice_update_dataset_group

Replaces the datasets in a dataset group with the specified datasets

frauddetector_create_model

Creates a model using the specified model type

forecastservice_describe_what_if_forecast_export

Describes the what-if forecast export created using the CreateWhatIfForecastExport operation

forecastservice_delete_predictor_backtest_export_job

Deletes a predictor backtest export job

forecastservice_describe_what_if_forecast

Describes the what-if forecast created using the CreateWhatIfForecast operation

forecastservice_delete_forecast_export_job

Deletes a forecast export job created using the CreateForecastExportJob operation

forecastservice_describe_explainability

Describes an Explainability resource created using the CreateExplainability operation

forecastservice_list_monitor_evaluations

Returns a list of the monitoring evaluation results and predictor events collected by the monitor resource during different windows of time

forecastservice_list_forecasts

Returns a list of forecasts created using the CreateForecast operation

comprehend_list_entity_recognizers

Gets a list of the properties of all entity recognizers that you created, including recognizers currently in training

forecastservice_delete_forecast

Deletes a forecast created using the CreateForecast operation

frauddetector_create_model_version

Creates a version of the model using the specified model type and model id

forecastservice_list_explainabilities

Returns a list of Explainability resources created using the CreateExplainability operation

forecastservice_list_monitors

Returns a list of monitors created with the CreateMonitor operation and CreateAutoPredictor operation

forecastservice_describe_dataset_import_job

Describes a dataset import job created using the CreateDatasetImportJob operation

forecastservice_delete_resource_tree

Deletes an entire resource tree

forecastservice_delete_what_if_analysis

Deletes a what-if analysis created using the CreateWhatIfAnalysis operation

forecastservice_tag_resource

Associates the specified tags to a resource with the specified resourceArn

frauddetector_delete_label

Deletes a label

frauddetector_delete_external_model

Removes a SageMaker model from Amazon Fraud Detector

frauddetector_cancel_batch_prediction_job

Cancels the specified batch prediction job

forecastservice_describe_predictor

This operation is only valid for legacy predictors created with CreatePredictor

frauddetector_delete_detector_version

Deletes the detector version

frauddetector_delete_detector

Deletes the detector

forecastservice_list_what_if_forecast_exports

Returns a list of what-if forecast exports created using the CreateWhatIfForecastExport operation

forecastservice_delete_monitor

Deletes a monitor resource

frauddetector_delete_event_type

Deletes an event type

frauddetector_cancel_batch_import_job

Cancels an in-progress batch import job

forecastservice_list_what_if_analyses

Returns a list of what-if analyses created using the CreateWhatIfAnalysis operation

frauddetector_create_detector_version

Creates a detector version

frauddetector_delete_outcome

Deletes an outcome

forecastservice_list_predictor_backtest_export_jobs

Returns a list of predictor backtest export jobs created using the CreatePredictorBacktestExportJob operation

comprehend_list_entity_recognizer_summaries

Gets a list of summaries for the entity recognizers that you have created

frauddetector_create_list

Creates a list

forecastservice_get_accuracy_metrics

Provides metrics on the accuracy of the models that were trained by the CreatePredictor operation

comprehend_start_entities_detection_job

Starts an asynchronous entity detection job for a collection of documents

frauddetector_delete_events_by_event_type

Deletes all events of a particular event type

frauddetector_delete_model

Deletes a model

frauddetector_get_delete_events_by_event_type_status

Retrieves the status of a DeleteEventsByEventType action

forecastservice_list_explainability_exports

Returns a list of Explainability exports created using the CreateExplainabilityExport operation

forecastservice_untag_resource

Deletes the specified tags from a resource

frauddetector_delete_list

Deletes the list, provided it is not used in a rule

frauddetector_list_event_predictions

Gets a list of past predictions

frauddetector_list_tags_for_resource

Lists all tags associated with the resource

frauddetector_describe_model_versions

Gets all of the model versions for the specified model type or for the specified model type and model ID

frauddetector_delete_batch_prediction_job

Deletes a batch prediction job

frauddetector_describe_detector

Gets all versions for a specified detector

frauddetector_delete_batch_import_job

Deletes the specified batch import job ID record

comprehend_start_events_detection_job

Starts an asynchronous event detection job for a collection of documents

frauddetector_delete_rule

Deletes the rule

comprehendmedical_start_phi_detection_job

Starts an asynchronous job to detect protected health information (PHI)

frauddetector_put_external_model

Creates or updates an Amazon SageMaker model endpoint

frauddetector_delete_variable

Deletes a variable

frauddetector_get_lists_metadata

Gets the metadata of either all the lists under the account or the specified list

frauddetector_get_detector_version

Gets a particular detector version

frauddetector_get_outcomes

Gets one or more outcomes

frauddetector_get_models

Gets one or more models

frauddetector_get_model_version

Gets the details of the specified model version

comprehendmedical_detect_entities_v2

Inspects the clinical text for a variety of medical entities and returns specific information about them such as entity category, location, and confidence score on that information

forecastservice_list_what_if_forecasts

Returns a list of what-if forecasts created using the CreateWhatIfForecast operation

frauddetector_tag_resource

Assigns tags to a resource

frauddetector_delete_model_version

Deletes a model version

frauddetector_get_detectors

Gets all detectors or a single detector if a detectorId is specified

frauddetector_update_detector_version_metadata

Updates the detector version's description

frauddetector_delete_entity_type

Deletes an entity type

frauddetector_get_entity_types

Gets all entity types or a specific entity type if a name is specified

lexmodelbuildingservice_create_slot_type_version

Creates a new version of a slot type based on the $LATEST version of the specified slot type

frauddetector_get_labels

Gets all labels or a specific label if name is provided

frauddetector_update_rule_metadata

Updates a rule's metadata

frauddetector_update_model_version

Updates a model version

frauddetector_get_event

Retrieves details of events stored with Amazon Fraud Detector

frauddetector_get_list_elements

Gets all the elements in the specified list

comprehendmedical_detect_phi

Inspects the clinical text for protected health information (PHI) entities and returns the entity category, location, and confidence score for each entity

frauddetector_update_rule_version

Updates a rule version resulting in a new rule version

frauddetector_batch_create_variable

Creates a batch of variables

frauddetector_untag_resource

Removes tags from a resource

frauddetector_batch_get_variable

Gets a batch of variables

frauddetector_get_batch_import_jobs

Gets all batch import jobs or a specific job of the specified ID

frauddetector_get_event_prediction

Evaluates an event against a detector version

frauddetector_update_detector_version

Updates a detector version

frauddetector_delete_event

Deletes the specified event

lexmodelbuildingservice_delete_bot

Deletes all versions of the bot, including the $LATEST version

frauddetector_get_batch_prediction_jobs

Gets all batch prediction jobs or a specific job if you specify a job ID

lexmodelbuildingservice_get_bot_aliases

Returns a list of aliases for a specified Amazon Lex bot

frauddetector_get_rules

Get all rules for a detector (paginated) if ruleId and ruleVersion are not specified

comprehendmedical_start_rx_norm_inference_job

Starts an asynchronous job to detect medication entities and link them to the RxNorm ontology

lexmodelbuildingservice_delete_slot_type_version

Deletes a specific version of a slot type

frauddetector_put_event_type

Creates or updates an event type

frauddetector_create_rule

Creates a rule for use with the specified detector

lexmodelbuildingservice

Amazon Lex Model Building Service

frauddetector_put_outcome

Creates or updates an outcome

lexmodelbuildingservice_get_builtin_intents

Gets a list of built-in intents that meet the specified criteria

lexmodelbuildingservice_get_builtin_slot_types

Gets a list of built-in slot types that meet the specified criteria

frauddetector_update_variable

Updates a variable

frauddetector_send_event

Stores events in Amazon Fraud Detector without generating fraud predictions for those events

lexmodelbuildingservice_delete_bot_channel_association

Deletes the association between an Amazon Lex bot and a messaging platform

lexmodelbuildingservice_put_bot

Creates an Amazon Lex conversational bot or replaces an existing bot

frauddetector_get_variables

Gets all of the variables or the specific variable

lexmodelbuildingservice_delete_bot_alias

Deletes an alias for the specified bot

frauddetector_update_model_version_status

Updates the status of a model version

lexmodelbuildingservice_get_intent

Returns information about an intent

lexmodelbuildingservice_delete_bot_version

Deletes a specific version of a bot

lexmodelbuildingservice_get_intent_versions

Gets information about all of the versions of an intent

forecastservice_create_what_if_forecast

A what-if forecast is a forecast that is created from a modified version of the baseline forecast

lexmodelbuildingservice_get_bot_channel_association

Returns information about the association between an Amazon Lex bot and a messaging platform

lexmodelbuildingservice_delete_utterances

Deletes stored utterances

forecastservice_create_what_if_forecast_export

Exports a forecast created by the CreateWhatIfForecast operation to your Amazon Simple Storage Service (Amazon S3) bucket

forecastservice_describe_auto_predictor

Describes a predictor created using the CreateAutoPredictor operation

comprehendmedical_stop_phi_detection_job

Stops a protected health information (PHI) detection job in progress

forecastservice_list_dataset_groups

Returns a list of dataset groups created using the CreateDatasetGroup operation

lexmodelbuildingservice_get_bot_channel_associations

Returns a list of all of the channels associated with the specified bot

lexmodelbuildingservice_get_bot_alias

Returns information about an Amazon Lex bot alias

forecastservice_describe_dataset

Describes an Amazon Forecast dataset created using the CreateDataset operation

frauddetector_get_external_models

Gets the details for one or more Amazon SageMaker models that have been imported into the service

frauddetector_create_variable

Creates a variable

lexmodelbuildingservice_get_slot_types

Returns slot type information as follows:

lexmodelbuildingservice_get_bot_versions

Gets information about all of the versions of a bot

lexmodelbuildingservice_get_slot_type_versions

Gets information about all versions of a slot type

frauddetector_get_event_prediction_metadata

Gets details of the past fraud predictions for the specified event ID, event type, detector ID, and detector version ID that was generated in the specified time period

frauddetector_get_event_types

Gets all event types or a specific event type if name is provided

lexmodelsv2_create_bot_locale

Creates a locale in the bot

frauddetector_put_kms_encryption_key

Specifies the KMS key to be used to encrypt content in Amazon Fraud Detector

lexmodelsv2_create_bot_alias

Creates an alias for the specified version of a bot

forecastservice_list_predictors

Returns a list of predictors created using the CreateAutoPredictor or CreatePredictor operations

lexmodelbuildingservice_get_import

Gets information about an import job started with the StartImport operation

frauddetector_put_label

Creates or updates label

lexmodelbuildingservice_get_migrations

Gets a list of migrations between Amazon Lex V1 and Amazon Lex V2

lexmodelbuildingservice_create_intent_version

Creates a new version of an intent based on the $LATEST version of the intent

lexmodelbuildingservice_tag_resource

Adds the specified tags to the specified resource

lexmodelbuildingservice_create_bot_version

Creates a new version of the bot based on the $LATEST version

lexmodelsv2_delete_bot

Deletes all versions of a bot, including the Draft version

lexmodelbuildingservice_get_utterances_view

Use the GetUtterancesView operation to get information about the utterances that your users have made to your bot

lexmodelsv2_delete_intent

Removes the specified intent

lexmodelsv2_delete_bot_alias

Deletes the specified bot alias

lexmodelbuildingservice_get_bots

Returns bot information as follows:

lexmodelbuildingservice_start_import

Starts a job to import a resource to Amazon Lex

lexmodelsv2_describe_bot_locale

Describes the settings that a bot has for a specific locale

lexmodelbuildingservice_get_migration

Provides details about an ongoing or complete migration from an Amazon Lex V1 bot to an Amazon Lex V2 bot

lexmodelbuildingservice_get_intents

Returns intent information as follows:

frauddetector_get_kms_encryption_key

Gets the encryption key if a KMS key has been specified to be used to encrypt content in Amazon Fraud Detector

frauddetector_put_detector

Creates or updates a detector

lexmodelbuildingservice_delete_intent_version

Deletes a specific version of an intent

lexmodelbuildingservice_get_builtin_intent

Returns information about a built-in intent

lexmodelsv2_delete_resource_policy

Removes an existing policy from a bot or bot alias

lexmodelbuildingservice_start_migration

Starts migrating a bot from Amazon Lex V1 to Amazon Lex V2

frauddetector_update_list

Updates a list

lexmodelsv2_delete_resource_policy_statement

Deletes a policy statement from a resource policy

frauddetector_update_detector_version_status

Updates the detector version’s status

frauddetector_put_entity_type

Creates or updates an entity type

frauddetector_update_model

Updates model description

lexmodelbuildingservice_get_export

Exports the contents of a Amazon Lex resource in a specified format

lexmodelbuildingservice_put_slot_type

Creates a custom slot type or replaces an existing custom slot type

frauddetector_update_event_label

Updates the specified event with a new label

lexmodelbuildingservice_put_intent

Creates an intent or replaces an existing intent

lexmodelbuildingservice_put_bot_alias

Creates an alias for the specified version of the bot or replaces an alias for the specified bot

lexmodelsv2_create_resource_policy

Creates a new resource policy with the specified policy statements

lexmodelsv2

Amazon Lex Model Building V2

lexmodelsv2_create_bot

Creates an Amazon Lex conversational bot

lexmodelbuildingservice_untag_resource

Removes tags from a bot, bot alias or bot channel

lexmodelbuildingservice_get_slot_type

Returns information about a specific version of a slot type

lexmodelsv2_describe_test_set

Gets metadata information about the test set

lexmodelsv2_create_bot_replica

Action to create a replication of the source bot in the secondary region

lexmodelsv2_create_bot_version

Creates an immutable version of the bot

lexmodelsv2_build_bot_locale

Builds a bot, its intents, and its slot types into a specific locale

lexmodelbuildingservice_delete_intent

Deletes all versions of the intent, including the $LATEST version

lexmodelsv2_create_test_set_discrepancy_report

Create a report that describes the differences between the bot and the test set

lexmodelsv2_describe_custom_vocabulary_metadata

Provides metadata information about a custom vocabulary

lexmodelsv2_batch_create_custom_vocabulary_item

Create a batch of custom vocabulary items for a given bot locale's custom vocabulary

lexmodelsv2_delete_slot_type

Deletes a slot type from a bot locale

lexmodelsv2_describe_resource_policy

Gets the resource policy and policy revision for a bot or bot alias

lexmodelbuildingservice_delete_slot_type

Deletes all versions of the slot type, including the $LATEST version

lexmodelsv2_list_test_execution_result_items

Gets a list of test execution result items

lexmodelsv2_create_export

Creates a zip archive containing the contents of a bot or a bot locale

lexmodelsv2_delete_export

Removes a previous export and the associated files stored in an S3 bucket

lexmodelsv2_describe_bot_version

Provides metadata about a version of a bot

lexmodelsv2_delete_slot

Deletes the specified slot from an intent

lexmodelsv2_create_intent

Creates an intent

lexmodelsv2_describe_bot_alias

Get information about a specific bot alias

lexmodelsv2_delete_utterances

Deletes stored utterances

lexmodelsv2_create_resource_policy_statement

Adds a new resource policy statement to a bot or bot alias

lexmodelsv2_delete_bot_replica

The action to delete the replicated bot in the secondary region

lexmodelsv2_describe_export

Gets information about a specific export

lexmodelsv2_list_bot_alias_replicas

The action to list the replicated bots created from the source bot alias

lexmodelsv2_list_slot_types

Gets a list of slot types that match the specified criteria

lexmodelsv2_create_upload_url

Gets a pre-signed S3 write URL that you use to upload the zip archive when importing a bot or a bot locale

lexmodelsv2_describe_bot

Provides metadata information about a bot

lexmodelsv2_list_exports

Lists the exports for a bot, bot locale, or custom vocabulary

lexmodelsv2_batch_delete_custom_vocabulary_item

Delete a batch of custom vocabulary items for a given bot locale's custom vocabulary

lexmodelsv2_delete_bot_locale

Removes a locale from a bot

lexmodelbuildingservice_get_bot

Returns metadata information for a specific bot

lexmodelbuildingservice_list_tags_for_resource

Gets a list of tags associated with the specified resource

lexmodelsv2_list_test_executions

The list of test set executions

lexmodelsv2_describe_bot_recommendation

Provides metadata information about a bot recommendation

lexmodelsv2_describe_test_set_discrepancy_report

Gets metadata information about the test set discrepancy report

lexmodelsv2_list_built_in_intents

Gets a list of built-in intents provided by Amazon Lex that you can use in your bot

lexmodelsv2_batch_update_custom_vocabulary_item

Update a batch of custom vocabulary items for a given bot locale's custom vocabulary

lexmodelsv2_list_bot_aliases

Gets a list of aliases for the specified bot

lexmodelsv2_list_intent_metrics

Retrieves summary metrics for the intents in your bot

lexmodelsv2_describe_import

Gets information about a specific import

lexmodelsv2_list_intent_paths

Retrieves summary statistics for a path of intents that users take over sessions with your bot

lexmodelsv2_delete_test_set

The action to delete the selected test set

lexmodelsv2_start_import

Starts importing a bot, bot locale, or custom vocabulary from a zip archive that you uploaded to an S3 bucket

lexmodelsv2_start_bot_resource_generation

Starts a request for the descriptive bot builder to generate a bot locale configuration based on the prompt you provide it

lexmodelsv2_list_test_set_records

The list of test set records

lexmodelsv2_create_slot

Creates a slot in an intent

lexmodelsv2_create_slot_type

Creates a custom slot type

lexmodelsv2_update_intent

Updates the settings for an intent

lexmodelsv2_list_bot_locales

Gets a list of locales for the specified bot

lexmodelsv2_list_bot_recommendations

Get a list of bot recommendations that meet the specified criteria

lexmodelsv2_delete_bot_version

Deletes a specific version of a bot

lexmodelsv2_list_test_sets

The list of the test sets

lexruntimeservice_get_session

Returns session information for a specified bot, alias, and user ID

lexmodelsv2_describe_test_set_generation

Gets metadata information about the test set generation

lexruntimeservice_delete_session

Removes session information for a specified bot, alias, and user ID

lexmodelsv2_update_resource_policy

Replaces the existing resource policy for a bot or bot alias with a new one

lexmodelsv2_list_utterance_analytics_data

To use this API operation, your IAM role must have permissions to perform the ListAggregatedUtterances operation, which provides access to utterance-related analytics

lexmodelsv2_describe_bot_replica

Monitors the bot replication status through the UI console

lexmodelsv2_describe_slot

Gets metadata information about a slot

lexmodelsv2_list_bots

Gets a list of available bots

lexmodelsv2_list_intent_stage_metrics

Retrieves summary metrics for the stages within intents in your bot

lexmodelsv2_list_session_metrics

Retrieves summary metrics for the user sessions with your bot

lexmodelsv2_delete_custom_vocabulary

Removes a custom vocabulary from the specified locale in the specified bot

lexmodelsv2_describe_test_execution

Gets metadata information about the test execution

lexruntimev2_recognize_text

Sends user input to Amazon Lex V2

lexruntimev2_put_session

Creates a new session or modifies an existing session with an Amazon Lex V2 bot

lexmodelsv2_describe_slot_type

Gets metadata information about a slot type

lexmodelsv2_delete_import

Removes a previous import and the associated file stored in an S3 bucket

lexmodelsv2_update_export

Updates the password used to protect an export zip archive

lexruntimeservice_post_content

Sends user input (text or speech) to Amazon Lex

lexmodelsv2_generate_bot_element

Generates sample utterances for an intent

lexmodelsv2_list_imports

Lists the imports for a bot, bot locale, or custom vocabulary

lexmodelsv2_start_bot_recommendation

Use this to provide your transcript data, and to start the bot recommendation process

lexmodelsv2_describe_bot_resource_generation

Returns information about a request to generate a bot through natural language description, made through the StartBotResource API

lexmodelsv2_list_bot_replicas

The action to list the replicated bots

lookoutequipment_create_retraining_scheduler

Creates a retraining scheduler on the specified model

lookoutequipment_delete_dataset

Deletes a dataset and associated artifacts

lexmodelsv2_update_bot_alias

Updates the configuration of an existing bot alias

lexmodelsv2_list_slots

Gets a list of slots that match the specified criteria

lexmodelsv2_search_associated_transcripts

Search for associated transcripts that meet the specified criteria

lexmodelsv2_get_test_execution_artifacts_url

The pre-signed Amazon S3 URL to download the test execution result artifacts

lookoutequipment_describe_data_ingestion_job

Provides information on a specific data ingestion job such as creation time, dataset ARN, and status

lookoutequipment_describe_dataset

Provides a JSON description of the data in each time series dataset, including names, column names, and data types

lexruntimeservice_post_text

Sends user input to Amazon Lex

lexmodelsv2_start_test_execution

The action to start test set execution

lexmodelsv2_list_bot_version_replicas

Contains information about all the versions replication statuses applicable for Global Resiliency

lexmodelsv2_describe_intent

Returns metadata about an intent

lexmodelsv2_list_bot_resource_generations

Lists the generation requests made for a bot locale

lexmodelsv2_update_bot_recommendation

Updates an existing bot recommendation request

lexmodelsv2_tag_resource

Adds the specified tags to the specified resource

lexmodelsv2_list_intents

Get a list of intents that meet the specified criteria

lexmodelsv2_list_utterance_metrics

To use this API operation, your IAM role must have permissions to perform the ListAggregatedUtterances operation, which provides access to utterance-related analytics

lookoutequipment

Amazon Lookout for Equipment

lookoutequipment_list_tags_for_resource

Lists all the tags for a specified resource, including key and value

lexruntimev2_delete_session

Removes session information for a specified bot, alias, and user ID

lookoutequipment_create_dataset

Creates a container for a collection of data being ingested for analysis

lookoutequipment_put_resource_policy

Creates a resource control policy for a given resource

lexmodelsv2_stop_bot_recommendation

Stop an already running Bot Recommendation request

lexmodelsv2_update_slot

Updates the settings for a slot

lexmodelsv2_list_aggregated_utterances

Provides a list of utterances that users have sent to the bot

lookoutequipment_untag_resource

Removes a specific tag from a given resource

lookoutequipment_list_datasets

Lists all datasets currently available in your account, filtering on the dataset name

lexmodelsv2_list_built_in_slot_types

Gets a list of built-in slot types that meet the specified criteria

lookoutequipment_list_inference_events

Lists all inference events that have been found for the specified inference scheduler

lookoutequipment_update_active_model_version

Sets the active model version for a given machine learning model

lexmodelsv2_list_session_analytics_data

Retrieves a list of metadata for individual user sessions with your bot

lookoutequipment_create_label_group

Creates a group of labels

lookoutequipment_import_model_version

Imports a model that has been trained successfully

lexmodelsv2_start_test_set_generation

The action to start the generation of test set

lexmodelsv2_list_recommended_intents

Gets a list of recommended intents provided by the bot recommendation that you can use in your bot

lexmodelsv2_list_custom_vocabulary_items

Paginated list of custom vocabulary items for a given bot locale's custom vocabulary

lexmodelsv2_list_bot_versions

Gets information about all of the versions of a bot

lookoutequipment_delete_label_group

Deletes a group of labels

lexmodelsv2_update_test_set

The action to update the test set

lexruntimev2_recognize_utterance

Sends user input to Amazon Lex V2

lexruntimev2_start_conversation

Starts an HTTP/2 bidirectional event stream that enables you to send audio, text, or DTMF input in real time

lexmodelsv2_untag_resource

Removes tags from a bot, bot alias, or bot channel

lexruntimeservice_put_session

Creates a new session or modifies an existing session with an Amazon Lex bot

lexruntimev2

Amazon Lex Runtime V2

lookoutequipment_start_inference_scheduler

Starts an inference scheduler

lexmodelsv2_update_bot

Updates the configuration of an existing bot

lexruntimeservice

Amazon Lex Runtime Service

lookoutequipment_describe_inference_scheduler

Specifies information about the inference scheduler being used, including name, model, status, and associated metadata

lookoutequipment_delete_model

Deletes a machine learning model currently available for Amazon Lookout for Equipment

lookoutequipment_list_inference_executions

Lists all inference executions that have been performed by the specified inference scheduler

lookoutequipment_describe_label_group

Returns information about the label group

lookoutequipment_create_model

Creates a machine learning model for data inference

lookoutequipment_describe_label

Returns the name of the label

lookoutmetrics

Amazon Lookout for Metrics

lookoutequipment_describe_model

Provides a JSON containing the overall information about a specific machine learning model, including model name and ARN, dataset, training and evaluation information, status, and so on

lookoutequipment_list_data_ingestion_jobs

Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on

lexmodelsv2_list_tags_for_resource

Gets a list of tags associated with a resource

lexruntimev2_get_session

Returns session information for a specified bot, alias, and user

lookoutmetrics_update_metric_set

Updates a dataset

lookoutequipment_create_inference_scheduler

Creates a scheduled inference

lookoutmetrics_delete_anomaly_detector

Deletes a detector

lookoutmetrics_get_anomaly_group

Returns details about a group of anomalous metrics

lookoutmetrics_describe_alert

Describes an alert

machinelearning_create_data_source_from_s3

Creates a DataSource object

lookoutequipment_tag_resource

Associates a given tag to a resource in your account

lookoutmetrics_get_data_quality_metrics

Returns details about the requested data quality metrics

lookoutmetrics_update_alert

Make changes to an existing alert

lookoutmetrics_create_alert

Creates an alert for an anomaly detector

lookoutequipment_list_inference_schedulers

Retrieves a list of all inference schedulers currently available for your account

machinelearning_create_evaluation

Creates a new Evaluation of an MLModel

lookoutmetrics_describe_anomaly_detector

Describes a detector

lookoutequipment_start_retraining_scheduler

Starts a retraining scheduler

lookoutmetrics_update_anomaly_detector

Updates a detector

lookoutmetrics_back_test_anomaly_detector

Runs a backtest for anomaly detection for the specified resource

lookoutequipment_stop_retraining_scheduler

Stops a retraining scheduler

lookoutmetrics_create_metric_set

Creates a dataset

lookoutequipment_stop_inference_scheduler

Stops an inference scheduler

lookoutequipment_delete_inference_scheduler

Deletes an inference scheduler that has been set up

machinelearning_create_data_source_from_rds

Creates a DataSource object from an Amazon Relational Database Service (Amazon RDS)

lookoutmetrics_create_anomaly_detector

Creates an anomaly detector

machinelearning_create_data_source_from_redshift

Creates a DataSource from a database hosted on an Amazon Redshift cluster

lookoutmetrics_detect_metric_set_config

Detects an Amazon S3 dataset's file format, interval, and offset

lookoutequipment_delete_label

Deletes a label

lookoutequipment_start_data_ingestion_job

Starts a data ingestion job

lookoutmetrics_describe_metric_set

Describes a dataset

machinelearning_describe_evaluations

Returns a list of DescribeEvaluations that match the search criteria in the request

lookoutmetrics_activate_anomaly_detector

Activates an anomaly detector

lookoutmetrics_get_sample_data

Returns a selection of sample records from an Amazon S3 datasource

lexmodelsv2_update_slot_type

Updates the configuration of an existing slot type

lookoutequipment_delete_resource_policy

Deletes the resource policy attached to the resource

lookoutmetrics_get_feedback

Get feedback for an anomaly group

lexmodelsv2_update_bot_locale

Updates the settings that a bot has for a specific locale

lookoutmetrics_list_alerts

Lists the alerts attached to a detector

panorama_describe_device

Returns information about a device

machinelearning_describe_ml_models

Returns a list of MLModel that match the search criteria in the request

lookoutmetrics_describe_anomaly_detection_executions

Returns information about the status of the specified anomaly detection jobs

machinelearning_create_batch_prediction

Generates predictions for a group of observations

panorama_describe_package

Returns information about a package

panorama_delete_package

Deletes a package

machinelearning_update_batch_prediction

Updates the BatchPredictionName of a BatchPrediction

machinelearning_update_data_source

Updates the DataSourceName of a DataSource

panorama_delete_device

Deletes a device

panorama_describe_node_from_template_job

Returns information about a job to create a camera stream node

machinelearning_delete_data_source

Assigns the DELETED status to a DataSource, rendering it unusable

machinelearning_add_tags

Adds one or more tags to an object, up to a limit of 10

lookoutmetrics_list_anomaly_group_time_series

Gets a list of anomalous metrics for a measure in an anomaly group

machinelearning_get_data_source

Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource

lookoutmetrics_put_feedback

Add feedback for an anomalous metric

lookoutmetrics_list_tags_for_resource

Gets a list of tags for a detector, dataset, or alert

lookoutmetrics_list_anomaly_detectors

Lists the detectors in the current AWS Region

panorama_list_application_instance_dependencies

Returns a list of application instance dependencies

lookoutequipment_create_label

Creates a label for an event

panorama_create_node_from_template_job

Creates a camera stream node

panorama_provision_device

Creates a device and returns a configuration archive

panorama_register_package_version

Registers a package version

personalize_create_campaign

You incur campaign costs while it is active

personalize_create_data_deletion_job

Creates a batch job that deletes all references to specific users from an Amazon Personalize dataset group in batches

panorama_signal_application_instance_node_instances

Signal camera nodes to stop or resume

panorama_describe_application_instance_details

Returns information about an application instance's configuration manifest

personalize_create_batch_inference_job

Generates batch recommendations based on a list of items or users stored in Amazon S3 and exports the recommendations to an Amazon S3 bucket

machinelearning_predict

Generates a prediction for the observation using the specified ML Model

personalize_create_batch_segment_job

Creates a batch segment job

panorama_remove_application_instance

Removes an application instance

machinelearning_get_ml_model

Returns an MLModel that includes detailed metadata, data source information, and the current status of the MLModel

machinelearning_delete_batch_prediction

Assigns the DELETED status to a BatchPrediction, rendering it unusable

personalize_create_metric_attribution

Creates a metric attribution

machinelearning_get_evaluation

Returns an Evaluation that includes metadata as well as the current status of the Evaluation

personalize_create_solution_version

Trains or retrains an active solution in a Custom dataset group

machinelearning_update_evaluation

Updates the EvaluationName of an Evaluation

personalize_create_recommender

Creates a recommender with the recipe (a Domain dataset group use case) you specify

machinelearning_delete_realtime_endpoint

Deletes a real time endpoint of an MLModel

lookoutmetrics_list_metric_sets

Lists the datasets in the current AWS Region

machinelearning_delete_tags

Deletes the specified tags associated with an ML object

lookoutmetrics_untag_resource

Removes tags from a detector, dataset, or alert

personalize_delete_metric_attribution

Deletes a metric attribution

panorama_create_package

Creates a package and storage location in an Amazon S3 access point

panorama_describe_package_import_job

Returns information about a package import job

panorama

AWS Panorama

lookoutmetrics_tag_resource

Adds tags to a detector, dataset, or alert

personalize_describe_batch_segment_job

Gets the properties of a batch segment job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate segments

panorama_describe_package_version

Returns information about a package version

panorama_list_tags_for_resource

Returns a list of tags for a resource

lookoutequipment_describe_resource_policy

Provides the details of a resource policy attached to a resource

panorama_create_package_import_job

Imports a node package

panorama_create_application_instance

Creates an application instance and deploys it to a device

machinelearning_update_ml_model

Updates the MLModelName and the ScoreThreshold of an MLModel

lookoutequipment_delete_retraining_scheduler

Deletes a retraining scheduler from a model

personalize_delete_filter

Deletes a filter

panorama_list_application_instance_node_instances

Returns a list of application node instances

personalize_describe_dataset

Describes the given dataset

personalize_describe_campaign

Describes the given campaign, including its status

panorama_describe_device_job

Returns information about a device job

personalize_delete_event_tracker

Deletes the event tracker

panorama_describe_node

Returns information about a node

personalize_delete_campaign

Removes a campaign by deleting the solution deployment

panorama_list_packages

Returns a list of packages

machinelearning_describe_data_sources

Returns a list of DataSource that match the search criteria in the request

lookoutequipment_describe_model_version

Retrieves information about a specific machine learning model version

lookoutequipment_describe_retraining_scheduler

Provides a description of the retraining scheduler, including information such as the model name and retraining parameters

lookoutequipment_list_model_versions

Generates a list of all model versions for a given model, including the model version, model version ARN, and status

personalize_describe_filter

Describes a filter's properties

personalize_create_dataset_group

Creates an empty dataset group

lookoutequipment_list_models

Generates a list of all models in the account, including model name and ARN, dataset, and status

lookoutequipment_import_dataset

Imports a dataset

lookoutequipment_update_model

Updates a model in the account

personalize_list_data_deletion_jobs

Returns a list of data deletion jobs for a dataset group ordered by creation time, with the most recent first

personalize_delete_solution

Deletes all versions of a solution and the Solution object itself

personalize_list_dataset_export_jobs

Returns a list of dataset export jobs that use the given dataset

personalize_delete_schema

Deletes a schema

personalize_list_filters

Lists all filters that belong to a given dataset group

machinelearning_describe_tags

Describes one or more of the tags for your Amazon ML object

personalize_describe_feature_transformation

Describes the given feature transformation

personalize_stop_recommender

Stops a recommender that is ACTIVE

personalize_list_batch_inference_jobs

Gets a list of the batch inference jobs that have been performed off of a solution version

personalize_get_solution_metrics

Gets the metrics for the specified solution version

personalize_create_event_tracker

Creates an event tracker that you use when adding event data to a specified dataset group using the PutEvents API

personalize_stop_solution_version_creation

Stops creating a solution version that is in a state of CREATE_PENDING or CREATE IN_PROGRESS

personalize_describe_data_deletion_job

Describes the data deletion job created by CreateDataDeletionJob, including the job status

panorama_create_job_for_devices

Creates a job to run on a device

personalize_list_schemas

Returns the list of schemas associated with the account

personalizeevents_put_action_interactions

Records action interaction event data

personalize

Amazon Personalize

panorama_update_device_metadata

Updates a device's metadata

machinelearning

Amazon Machine Learning

personalizeevents_put_actions

Adds one or more actions to an Actions dataset

machinelearning_delete_evaluation

Assigns the DELETED status to an Evaluation, rendering it unusable

lookoutequipment_update_retraining_scheduler

Updates a retraining scheduler

machinelearning_get_batch_prediction

Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request

polly

Amazon Polly

panorama_list_node_from_template_jobs

Returns a list of camera stream node jobs

lookoutequipment_list_labels

Provides a list of labels

personalize_describe_solution_version

Describes a specific version of a solution

lookoutequipment_list_label_groups

Returns a list of the label groups

personalize_list_metric_attribution_metrics

Lists the metrics for the metric attribution

personalizeruntime_get_recommendations

Returns a list of recommended items

lookoutequipment_list_retraining_schedulers

Lists all retraining schedulers in your account, filtering by model name prefix and status

personalize_list_campaigns

Returns a list of campaigns that use the given solution

machinelearning_delete_ml_model

Assigns the DELETED status to an MLModel, rendering it unusable

personalize_describe_dataset_import_job

Describes the dataset import job created by CreateDatasetImportJob, including the import job status

personalize_describe_solution

Describes a solution

personalize_create_filter

Creates a recommendation filter

personalize_delete_recommender

Deactivates and removes a recommender

personalize_list_recommenders

Returns a list of recommenders in a given Domain dataset group

lookoutmetrics_deactivate_anomaly_detector

Deactivates an anomaly detector

lookoutequipment_list_sensor_statistics

Lists statistics about the data collected for each of the sensors that have been successfully ingested in the particular dataset

polly_put_lexicon

Stores a pronunciation lexicon in an Amazon Web Services Region

personalize_create_dataset_export_job

Creates a job that exports data from your dataset to an Amazon S3 bucket

personalize_untag_resource

Removes the specified tags that are attached to a resource

personalize_list_metric_attributions

Lists metric attributions

personalize_list_solution_versions

Returns a list of solution versions for the given solution

polly_start_speech_synthesis_task

Allows the creation of an asynchronous synthesis task, by starting a new SpeechSynthesisTask

lookoutequipment_update_inference_scheduler

Updates an inference scheduler

personalize_describe_event_tracker

Describes an event tracker

personalize_list_recipes

Returns a list of available recipes

panorama_list_devices

Returns a list of devices

panorama_list_nodes

Returns a list of nodes

lookoutmetrics_delete_alert

Deletes an alert

lookoutequipment_update_label_group

Updates the label group

personalize_delete_dataset

Deletes a dataset

panorama_tag_resource

Tags a resource

personalize_list_batch_segment_jobs

Gets a list of the batch segment jobs that have been performed off of a solution version that you specify

personalizeruntime_get_action_recommendations

Returns a list of recommended actions in sorted in descending order by prediction score

lookoutmetrics_list_anomaly_group_related_metrics

Returns a list of measures that are potential causes or effects of an anomaly group

rekognition_delete_collection

Deletes the specified collection

panorama_list_application_instances

Returns a list of application instances

rekognition_create_user

Creates a new User within a collection specified by CollectionId

personalize_list_solutions

Returns a list of solutions in a given dataset group

rekognition_describe_dataset

This operation applies only to Amazon Rekognition Custom Labels

lookoutmetrics_list_anomaly_group_summaries

Returns a list of anomaly groups

personalize_list_tags_for_resource

Get a list of tags attached to a resource

personalize_update_metric_attribution

Updates a metric attribution

personalize_start_recommender

Starts a recommender that is INACTIVE

rekognition_create_collection

Creates a collection in an AWS Region

personalizeruntime_get_personalized_ranking

Re-ranks a list of recommended items for the given user

rekognition_detect_protective_equipment

Detects Personal Protective Equipment (PPE) worn by people detected in an image

rekognition_describe_project_versions

Lists and describes the versions of an Amazon Rekognition project

panorama_list_devices_jobs

Returns a list of jobs

rekognition_detect_text

Detects text in the input image and converts it into machine-readable text

personalize_update_campaign

Updates a campaign to deploy a retrained solution version with an existing campaign, change your campaign's minProvisionedTPS, or modify your campaign's configuration

personalize_update_dataset

Update a dataset to replace its schema with a new or existing one

personalizeevents

Amazon Personalize Events

rekognition_get_person_tracking

Gets the path tracking results of a Amazon Rekognition Video analysis started by StartPersonTracking

rekognition_delete_user

Deletes the specified UserID within the collection

panorama_untag_resource

Removes tags from a resource

personalize_update_solution

Updates an Amazon Personalize solution to use a different automatic training configuration

personalize_describe_algorithm

Describes the given algorithm

personalize_create_dataset_import_job

Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset

rekognition_compare_faces

Compares a face in the source input image with each of the 100 largest faces detected in the target input image

rekognition_disassociate_faces

Removes the association between a Face supplied in an array of FaceIds and the User

rekognition_list_collections

Returns list of collection IDs in your account

rekognition_copy_project_version

This operation applies only to Amazon Rekognition Custom Labels

machinelearning_create_ml_model

Creates a new MLModel using the DataSource and the recipe as information sources

machinelearning_create_realtime_endpoint

Creates a real-time endpoint for the MLModel

rekognition_list_faces

Returns metadata for faces in the specified collection

machinelearning_describe_batch_predictions

Returns a list of BatchPrediction operations that match the search criteria in the request

personalize_update_recommender

Updates the recommender to modify the recommender configuration

panorama_deregister_package_version

Deregisters a package version

rekognition_create_project

Creates a new Amazon Rekognition project

panorama_describe_application_instance

Returns information about an application instance on a device

rekognition_search_faces_by_image

For a given input image, first detects the largest face in the image, and then searches the specified collection for matching faces

rekognition_recognize_celebrities

Returns an array of celebrities recognized in the input image

personalize_describe_recipe

Describes a recipe

personalize_delete_dataset_group

Deletes a dataset group

polly_list_lexicons

Returns a list of pronunciation lexicons stored in an Amazon Web Services Region

polly_synthesize_speech

Synthesizes UTF-8 input, plain text or SSML, to a stream of bytes

polly_list_speech_synthesis_tasks

Returns a list of SpeechSynthesisTask objects ordered by their creation date

rekognition_get_text_detection

Gets the text detection results of a Amazon Rekognition Video analysis started by StartTextDetection

reexports

Objects exported from other packages

rekognition_delete_project_version

Deletes a Rekognition project model or project version, like a Amazon Rekognition Custom Labels model or a custom adapter

rekognition_get_content_moderation

Gets the inappropriate, unwanted, or offensive content analysis results for a Amazon Rekognition Video analysis started by StartContentModeration

rekognition_describe_collection

Describes the specified collection

rekognition_distribute_dataset_entries

This operation applies only to Amazon Rekognition Custom Labels

rekognition_create_face_liveness_session

This API operation initiates a Face Liveness session

personalize_create_schema

Creates an Amazon Personalize schema from the specified schema string

rekognition_start_content_moderation

Starts asynchronous detection of inappropriate, unwanted, or offensive content in a stored video

rekognition_delete_stream_processor

Deletes the stream processor identified by Name

rekognition_delete_dataset

This operation applies only to Amazon Rekognition Custom Labels

personalize_describe_recommender

Describes the given recommender, including its status

rekognition_delete_faces

Deletes faces from a collection

rekognition_detect_moderation_labels

Detects unsafe content in a specified JPEG or PNG format image

rekognition_detect_labels

Detects instances of real-world entities within an image (JPEG or PNG) provided as input

rekognition_get_segment_detection

Gets the segment detection results of a Amazon Rekognition Video analysis started by StartSegmentDetection

rekognition_create_dataset

This operation applies only to Amazon Rekognition Custom Labels

rekognition_search_users

Searches for UserIDs within a collection based on a FaceId or UserId

rekognition_index_faces

Detects faces in the input image and adds them to the specified collection

rekognition_update_dataset_entries

This operation applies only to Amazon Rekognition Custom Labels

rekognition_update_stream_processor

Allows you to update a stream processor

personalize_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

sagemaker_add_tags

Adds or overwrites one or more tags for the specified SageMaker resource

rekognition_start_label_detection

Starts asynchronous detection of labels in a stored video

personalize_describe_dataset_export_job

Describes the dataset export job created by CreateDatasetExportJob, including the export job status

rekognition_delete_project

Deletes a Amazon Rekognition project

personalizeevents_put_users

Adds one or more users to a Users dataset

personalize_list_datasets

Returns the list of datasets contained in the given dataset group

personalize_describe_dataset_group

Describes the given dataset group

sagemaker_associate_trial_component

Associates a trial component with a trial

polly_delete_lexicon

Deletes the specified pronunciation lexicon stored in an Amazon Web Services Region

rekognition_detect_faces

Detects faces within an image that is provided as input

rekognition_get_label_detection

Gets the label detection results of a Amazon Rekognition Video analysis started by StartLabelDetection

rekognition_detect_custom_labels

This operation applies only to Amazon Rekognition Custom Labels

personalize_tag_resource

Add a list of tags to a resource

rekognition_start_stream_processor

Starts processing a stream processor

personalize_list_event_trackers

Returns the list of event trackers associated with the account

rekognition_get_media_analysis_job

Retrieves the results for a given media analysis job

rekognition_search_faces

For a given input face ID, searches for matching faces in the collection the face belongs to

personalizeruntime

Amazon Personalize Runtime

polly_describe_voices

Returns the list of voices that are available for use when requesting speech synthesis

rekognition_get_face_search

Gets the face search results for Amazon Rekognition Video face search started by StartFaceSearch

rekognition_put_project_policy

This operation applies only to Amazon Rekognition Custom Labels

rekognition_list_users

Returns metadata of the User such as UserID in the specified collection

sagemaker_create_cluster_scheduler_config

Create cluster policy configuration

panorama_list_package_import_jobs

Returns a list of package import jobs

rekognition_start_face_search

Starts the asynchronous search for faces in a collection that match the faces of persons detected in a stored video

rekognition_delete_project_policy

This operation applies only to Amazon Rekognition Custom Labels

rekognition_stop_project_version

This operation applies only to Amazon Rekognition Custom Labels

rekognition_list_stream_processors

Gets a list of stream processors that you have created with CreateStreamProcessor

sagemaker_create_experiment

Creates a SageMaker experiment

rekognition_get_face_detection

Gets face detection results for a Amazon Rekognition Video analysis started by StartFaceDetection

sagemaker_create_code_repository

Creates a Git repository as a resource in your SageMaker AI account

rekognition_stop_stream_processor

Stops a running stream processor that was created by CreateStreamProcessor

sagemaker_create_endpoint_config

Creates an endpoint configuration that SageMaker hosting services uses to deploy models

rekognition_get_face_liveness_session_results

Retrieves the results of a specific Face Liveness session

sagemaker_create_artifact

Creates an artifact

rekognition_untag_resource

Removes one or more tags from an Amazon Rekognition collection, stream processor, or Custom Labels model

rekognition_tag_resource

Adds one or more key-value tags to an Amazon Rekognition collection, stream processor, or Custom Labels model

sagemaker_create_human_task_ui

Defines the settings you will use for the human review workflow user interface

rekognition_list_tags_for_resource

Returns a list of tags in an Amazon Rekognition collection, stream processor, or Custom Labels model

sagemaker_create_auto_ml_job

Creates an Autopilot job also referred to as Autopilot experiment or AutoML job

sagemaker_create_hyper_parameter_tuning_job

Starts a hyperparameter tuning job

personalize_create_solution

By default, all new solutions use automatic training

personalize_create_dataset

Creates an empty dataset and adds it to the specified dataset group

rekognition_start_face_detection

Starts asynchronous detection of faces in a stored video

rekognition_list_dataset_labels

This operation applies only to Amazon Rekognition Custom Labels

personalize_describe_metric_attribution

Describes a metric attribution

personalizeevents_put_events

Records item interaction event data

sagemaker_create_context

Creates a context

sagemaker_create_data_quality_job_definition

Creates a definition for a job that monitors data quality and drift

rekognition_create_stream_processor

Creates an Amazon Rekognition stream processor that you can use to detect and recognize faces or to detect labels in a streaming video

sagemaker_create_model_quality_job_definition

Creates a definition for a job that monitors model quality and drift

rekognition_start_media_analysis_job

Initiates a new media analysis job

personalizeevents_put_items

Adds one or more items to an Items dataset

personalize_list_dataset_groups

Returns a list of dataset groups

personalize_describe_schema

Describes a schema

sagemaker_create_image

Creates a custom SageMaker AI image

sagemaker_create_model_package

Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group

sagemaker_create_algorithm

Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace

sagemaker_create_hub

Create a hub

sagemaker_create_action

Creates an action

sagemaker_batch_delete_cluster_nodes

Deletes specific nodes within a SageMaker HyperPod cluster

sagemaker_create_edge_packaging_job

Starts a SageMaker Edge Manager model packaging job

sagemaker_create_labeling_job

Creates a job that uses workers to label the data objects in your input dataset

sagemaker_create_inference_recommendations_job

Starts a recommendation job

personalize_list_dataset_import_jobs

Returns a list of dataset import jobs that use the given dataset

polly_get_speech_synthesis_task

Retrieves a specific SpeechSynthesisTask object based on its TaskID

sagemaker_create_endpoint

Creates an endpoint using the endpoint configuration specified in the request

sagemaker_batch_describe_model_package

This action batch describes a list of versioned model packages

sagemaker_create_edge_deployment_plan

Creates an edge deployment plan, consisting of multiple stages

sagemaker_create_edge_deployment_stage

Creates a new stage in an existing edge deployment plan

sagemaker_create_model_card_export_job

Creates an Amazon SageMaker Model Card export job

polly_get_lexicon

Returns the content of the specified pronunciation lexicon stored in an Amazon Web Services Region

sagemaker_create_auto_ml_job_v2

Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2

rekognition_list_dataset_entries

This operation applies only to Amazon Rekognition Custom Labels

sagemaker_create_image_version

Creates a version of the SageMaker AI image specified by ImageName

sagemaker_create_workforce

Use this operation to create a workforce

sagemaker_create_model_package_group

Creates a model group

sagemaker_create_user_profile

Creates a user profile

sagemaker_create_partner_app_presigned_url

Creates a presigned URL to access an Amazon SageMaker Partner AI App

sagemaker_create_monitoring_schedule

Creates a schedule that regularly starts Amazon SageMaker AI Processing Jobs to monitor the data captured for an Amazon SageMaker AI Endpoint

sagemaker_create_cluster

Creates a SageMaker HyperPod cluster

sagemaker_create_training_plan

Creates a new training plan in SageMaker to reserve compute capacity

sagemaker_delete_device_fleet

Deletes a fleet

sagemaker_create_domain

Creates a Domain

sagemaker_delete_code_repository

Deletes the specified Git repository from your account

sagemaker_delete_cluster_scheduler_config

Deletes the cluster policy of the cluster

sagemaker_create_device_fleet

Creates a device fleet

rekognition

Amazon Rekognition

rekognition_associate_faces

Associates one or more faces with an existing UserID

sagemaker_create_presigned_notebook_instance_url

Returns a URL that you can use to connect to the Jupyter server from a notebook instance

rekognition_create_project_version

Creates a new version of Amazon Rekognition project (like a Custom Labels model or a custom adapter) and begins training

sagemaker_delete_domain

Used to delete a domain

sagemaker_create_pipeline

Creates a pipeline using a JSON pipeline definition

sagemaker_create_hub_content_reference

Create a hub content reference in order to add a model in the JumpStart public hub to a private hub

sagemaker_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

sagemaker_create_model_explainability_job_definition

Creates the definition for a model explainability job

sagemaker_delete_action

Deletes an action

sagemaker_create_compute_quota

Create compute allocation definition

sagemaker_create_workteam

Creates a new work team for labeling your data

sagemaker_create_space

Creates a private space or a space used for real time collaboration in a domain

rekognition_get_celebrity_recognition

Gets the celebrity recognition results for a Amazon Rekognition Video analysis started by StartCelebrityRecognition

sagemaker_create_presigned_domain_url

Creates a URL for a specified UserProfile in a Domain

sagemaker_delete_experiment

Deletes an SageMaker experiment

rekognition_describe_projects

Gets information about your Rekognition projects

rekognition_describe_stream_processor

Provides information about a stream processor created by CreateStreamProcessor

sagemaker_create_model_bias_job_definition

Creates the definition for a model bias job

rekognition_get_celebrity_info

Gets the name and additional information about a celebrity based on their Amazon Rekognition ID

rekognition_list_project_policies

This operation applies only to Amazon Rekognition Custom Labels

rekognition_start_segment_detection

Starts asynchronous detection of segment detection in a stored video

sagemaker_create_trial_component

Creates a trial component, which is a stage of a machine learning trial

rekognition_start_project_version

This operation applies only to Amazon Rekognition Custom Labels

rekognition_start_person_tracking

Starts the asynchronous tracking of a person's path in a stored video

sagemaker_delete_feature_group

Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup

rekognition_list_media_analysis_jobs

Returns a list of media analysis jobs

sagemaker_create_app_image_config

Creates a configuration for running a SageMaker AI image as a KernelGateway app

rekognition_search_users_by_image

Searches for UserIDs using a supplied image

sagemaker_create_trial

Creates an SageMaker trial

sagemaker_delete_pipeline

Deletes a pipeline if there are no running instances of the pipeline

sagemaker_create_presigned_mlflow_tracking_server_url

Returns a presigned URL that you can use to connect to the MLflow UI attached to your tracking server

sagemaker_delete_app_image_config

Deletes an AppImageConfig

sagemaker

Amazon SageMaker Service

sagemaker_describe_auto_ml_job

Returns information about an AutoML job created by calling CreateAutoMLJob

rekognition_start_text_detection

Starts asynchronous detection of text in a stored video

sagemaker_delete_endpoint

Deletes an endpoint

sagemaker_delete_trial_component

Deletes the specified trial component

rekognition_start_celebrity_recognition

Starts asynchronous recognition of celebrities in a stored video

sagemaker_delete_artifact

Deletes an artifact

sagemaker_delete_data_quality_job_definition

Deletes a data quality monitoring job definition

sagemaker_delete_context

Deletes an context

sagemaker_create_app

Creates a running app for the specified UserProfile

sagemaker_delete_model_package_group

Deletes the specified model group

sagemaker_delete_human_task_ui

Use this operation to delete a human task user interface (worker task template)

sagemaker_delete_hyper_parameter_tuning_job

Deletes a hyperparameter tuning job

sagemaker_delete_model

Deletes a model

sagemaker_create_notebook_instance_lifecycle_config

Creates a lifecycle configuration that you can associate with a notebook instance

sagemaker_delete_mlflow_tracking_server

Deletes an MLflow Tracking Server

sagemaker_delete_flow_definition

Deletes the specified flow definition

sagemaker_create_optimization_job

Creates a job that optimizes a model for inference performance

sagemaker_create_partner_app

Creates an Amazon SageMaker Partner AI App

sagemaker_delete_edge_deployment_plan

Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive or there are no stages in the plan

sagemaker_delete_monitoring_schedule

Deletes a monitoring schedule

sagemaker_create_feature_group

Create a new FeatureGroup

sagemaker_add_association

Creates an association between the source and the destination

sagemaker_create_inference_experiment

Creates an inference experiment using the configurations specified in the request

sagemaker_create_compilation_job

Starts a model compilation job

sagemaker_delete_hub

Delete a hub

sagemaker_delete_user_profile

Deletes a user profile

sagemaker_describe_auto_ml_job_v2

Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob

sagemaker_delete_inference_component

Deletes an inference component

sagemaker_delete_model_explainability_job_definition

Deletes an Amazon SageMaker AI model explainability job definition

sagemaker_create_transform_job

Starts a transform job

sagemaker_delete_image

Deletes a SageMaker AI image and all versions of the image

sagemaker_delete_algorithm

Removes the specified algorithm from your account

sagemaker_create_flow_definition

Creates a flow definition

sagemaker_delete_inference_experiment

Deletes an inference experiment

sagemaker_delete_optimization_job

Deletes an optimization job

sagemaker_delete_endpoint_config

Deletes an endpoint configuration

sagemaker_describe_model_card_export_job

Describes an Amazon SageMaker Model Card export job

sagemaker_create_model

Creates a model in SageMaker

sagemaker_delete_app

Used to stop and delete an app

sagemaker_create_inference_component

Creates an inference component, which is a SageMaker AI hosting object that you can use to deploy a model to an endpoint

sagemaker_create_mlflow_tracking_server

Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact store

sagemaker_create_studio_lifecycle_config

Creates a new Amazon SageMaker AI Studio Lifecycle Configuration

sagemaker_create_notebook_instance

Creates an SageMaker AI notebook instance

sagemaker_delete_partner_app

Deletes a SageMaker Partner AI App

sagemaker_create_training_job

Starts a model training job

sagemaker_describe_pipeline

Describes the details of a pipeline

sagemaker_delete_association

Deletes an association

sagemaker_delete_model_bias_job_definition

Deletes an Amazon SageMaker AI model bias job definition

sagemaker_describe_model_quality_job_definition

Returns a description of a model quality job definition

sagemaker_describe_device

Describes the device

sagemaker_delete_project

Delete the specified project

sagemaker_describe_device_fleet

A description of the fleet the device belongs to

sagemaker_describe_human_task_ui

Returns information about the requested human task user interface (worker task template)

sagemaker_delete_hub_content

Delete the contents of a hub

sagemaker_describe_endpoint_config

Returns the description of an endpoint configuration created using the CreateEndpointConfig API

sagemaker_delete_cluster

Delete a SageMaker HyperPod cluster

sagemaker_describe_cluster_scheduler_config

Description of the cluster policy

sagemaker_delete_image_version

Deletes a version of a SageMaker AI image

sagemaker_get_lineage_group_policy

The resource policy for the lineage group

sagemaker_deregister_devices

Deregisters the specified devices

sagemaker_delete_edge_deployment_stage

Delete a stage in an edge deployment plan if (and only if) the stage is inactive

sagemaker_describe_action

Describes an action

sagemaker_describe_pipeline_execution

Describes the details of a pipeline execution

sagemaker_list_algorithms

Lists the machine learning algorithms that have been created

sagemaker_describe_processing_job

Returns a description of a processing job

sagemaker_describe_monitoring_schedule

Describes the schedule for a monitoring job

sagemaker_create_model_card

Creates an Amazon SageMaker Model Card

sagemaker_describe_workforce

Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs)

sagemaker_delete_model_card

Deletes an Amazon SageMaker Model Card

sagemaker_describe_experiment

Provides a list of an experiment's properties

sagemaker_describe_model_bias_job_definition

Returns a description of a model bias job definition

sagemaker_delete_hub_content_reference

Delete a hub content reference in order to remove a model from a private hub

sagemaker_describe_code_repository

Gets details about the specified Git repository

sagemaker_describe_algorithm

Returns a description of the specified algorithm that is in your account

sagemaker_describe_workteam

Gets information about a specific work team

sagemaker_list_code_repositories

Gets a list of the Git repositories in your account

sagemaker_create_processing_job

Creates a processing job

sagemaker_describe_hub_content

Describe the content of a hub

sagemaker_delete_model_quality_job_definition

Deletes the secified model quality monitoring job definition

sagemaker_describe_app

Describes the app

sagemaker_describe_image_version

Describes a version of a SageMaker AI image

sagemaker_delete_compilation_job

Deletes the specified compilation job

sagemaker_delete_compute_quota

Deletes the compute allocation from the cluster

sagemaker_delete_space

Used to delete a space

sagemaker_describe_app_image_config

Describes an AppImageConfig

sagemaker_describe_flow_definition

Returns information about the specified flow definition

sagemaker_describe_artifact

Describes an artifact

sagemaker_describe_context

Describes a context

sagemaker_describe_inference_recommendations_job

Provides the results of the Inference Recommender job

sagemaker_delete_model_package_group_policy

Deletes a model group resource policy

sagemaker_describe_compute_quota

Description of the compute allocation definition

sagemaker_describe_transform_job

Returns information about a transform job

sagemaker_describe_edge_packaging_job

A description of edge packaging jobs

sagemaker_describe_training_job

Returns information about a training job

sagemaker_describe_endpoint

Returns the description of an endpoint

sagemaker_describe_model_explainability_job_definition

Returns a description of a model explainability job definition

sagemaker_describe_feature_metadata

Shows the metadata for a feature within a feature group

sagemaker_describe_user_profile

Describes a user profile

sagemaker_get_sagemaker_servicecatalog_portfolio_status

Gets the status of Service Catalog in SageMaker

sagemaker_describe_training_plan

Retrieves detailed information about a specific training plan

sagemaker_describe_trial_component

Provides a list of a trials component's properties

sagemaker_describe_feature_group

Use this operation to describe a FeatureGroup

sagemaker_describe_hub

Describes a hub

sagemaker_list_compilation_jobs

Lists model compilation jobs that satisfy various filters

sagemaker_get_model_package_group_policy

Gets a resource policy that manages access for a model group

sagemaker_delete_model_package

Deletes a model package

sagemaker_describe_model_card

Describes the content, creation time, and security configuration of an Amazon SageMaker Model Card

sagemaker_list_hyper_parameter_tuning_jobs

Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account

sagemaker_list_actions

Lists the actions in your account and their properties

sagemaker_list_edge_packaging_jobs

Returns a list of edge packaging jobs

sagemaker_list_edge_deployment_plans

Lists all edge deployment plans

sagemaker_describe_trial

Provides a list of a trial's properties

sagemaker_describe_model_package

Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace

sagemaker_list_candidates_for_auto_ml_job

List the candidates created for the job

sagemaker_delete_notebook_instance

Deletes an SageMaker AI notebook instance

sagemaker_list_auto_ml_jobs

Request a list of jobs

sagemaker_list_cluster_nodes

Retrieves the list of instances (also called nodes interchangeably) in a SageMaker HyperPod cluster

sagemaker_list_model_card_versions

List existing versions of an Amazon SageMaker Model Card

sagemaker_describe_domain

The description of the domain

sagemaker_list_model_quality_job_definitions

Gets a list of model quality monitoring job definitions in your account

sagemaker_delete_studio_lifecycle_config

Deletes the Amazon SageMaker AI Studio Lifecycle Configuration

sagemaker_describe_model_package_group

Gets a description for the specified model group

sagemaker_list_inference_recommendations_jobs

Lists recommendation jobs that satisfy various filters

sagemaker_list_optimization_jobs

Lists the optimization jobs in your account and their properties

sagemaker_list_inference_recommendations_job_steps

Returns a list of the subtasks for an Inference Recommender job

sagemaker_get_scaling_configuration_recommendation

Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job

sagemaker_delete_tags

Deletes the specified tags from an SageMaker resource

sagemaker_list_models

Lists models created with the CreateModel API

sagemaker_list_device_fleets

Returns a list of devices in the fleet

sagemaker_list_data_quality_job_definitions

Lists the data quality job definitions in your account

sagemaker_list_partner_apps

Lists all of the SageMaker Partner AI Apps in an account

sagemaker_list_image_versions

Lists the versions of a specified image and their properties

sagemaker_delete_trial

Deletes the specified trial

sagemaker_list_images

Lists the images in your account and their properties

sagemaker_list_stage_devices

Lists devices allocated to the stage, containing detailed device information and deployment status

sagemaker_list_human_task_uis

Returns information about the human task user interfaces in your account

sagemaker_get_device_fleet_report

Describes a fleet

sagemaker_enable_sagemaker_servicecatalog_portfolio

Enables using Service Catalog in SageMaker

sagemaker_list_model_metadata

Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos

sagemaker_describe_project

Describes the details of a project

sagemaker_list_model_explainability_job_definitions

Lists model explainability job definitions that satisfy various filters

sagemaker_describe_edge_deployment_plan

Describes an edge deployment plan with deployment status per stage

sagemaker_describe_inference_component

Returns information about an inference component

sagemaker_list_labeling_jobs_for_workteam

Gets a list of labeling jobs assigned to a specified work team

sagemaker_list_labeling_jobs

Gets a list of labeling jobs

sagemaker_describe_inference_experiment

Returns details about an inference experiment

sagemaker_describe_compilation_job

Returns information about a model compilation job

sagemaker_list_model_cards

List existing model cards

sagemaker_list_training_plans

Retrieves a list of training plans for the current account

sagemaker_delete_workforce

Use this operation to delete a workforce

sagemaker_list_transform_jobs

Lists transform jobs

sagemaker_list_cluster_scheduler_configs

List the cluster policy configurations

sagemaker_list_model_bias_job_definitions

Lists model bias jobs definitions that satisfy various filters

sagemaker_list_pipeline_parameters_for_execution

Gets a list of parameters for a pipeline execution

sagemaker_list_pipelines

Gets a list of pipelines

sagemaker_list_studio_lifecycle_configs

Lists the Amazon SageMaker AI Studio Lifecycle Configurations in your Amazon Web Services Account

sagemaker_describe_notebook_instance

Returns information about a notebook instance

sagemaker_delete_notebook_instance_lifecycle_config

Deletes a notebook instance lifecycle configuration

sagemaker_describe_cluster

Retrieves information of a SageMaker HyperPod cluster

sagemaker_delete_workteam

Deletes an existing work team

sagemaker_describe_mlflow_tracking_server

Returns information about an MLflow Tracking Server

sagemaker_list_hub_contents

List the contents of a hub

sagemaker_start_mlflow_tracking_server

Programmatically start an MLflow Tracking Server

sagemaker_describe_cluster_node

Retrieves information of a node (also called a instance interchangeably) of a SageMaker HyperPod cluster

sagemaker_stop_inference_experiment

Stops an inference experiment

sagemaker_stop_hyper_parameter_tuning_job

Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched

sagemaker_list_apps

Lists apps

sagemaker_describe_space

Describes the space

sagemaker_list_clusters

Retrieves the list of SageMaker HyperPod clusters

sagemaker_list_artifacts

Lists the artifacts in your account and their properties

sagemaker_get_search_suggestions

An auto-complete API for the search functionality in the SageMaker console

sagemaker_describe_notebook_instance_lifecycle_config

Returns a description of a notebook instance lifecycle configuration

sagemaker_list_projects

Gets a list of the projects in an Amazon Web Services account

sagemaker_describe_lineage_group

Provides a list of properties for the requested lineage group

sagemaker_update_cluster

Updates a SageMaker HyperPod cluster

sagemaker_describe_studio_lifecycle_config

Describes the Amazon SageMaker AI Studio Lifecycle Configuration

sagemaker_update_artifact

Updates an artifact

sagemaker_update_cluster_scheduler_config

Update the cluster policy configuration

sagemaker_describe_data_quality_job_definition

Gets the details of a data quality monitoring job definition

sagemaker_list_trial_components

Lists the trial components in your account

sagemaker_stop_mlflow_tracking_server

Programmatically stop an MLflow Tracking Server

sagemaker_list_subscribed_workteams

Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace

sagemaker_describe_labeling_job

Gets information about a labeling job

sagemaker_send_pipeline_execution_step_failure

Notifies the pipeline that the execution of a callback step failed, along with a message describing why

sagemaker_stop_auto_ml_job

A method for forcing a running job to shut down

sagemaker_list_tags

Returns the tags for the specified SageMaker resource

sagemaker_list_hub_content_versions

List hub content versions

sagemaker_list_devices

A list of devices

sagemaker_start_edge_deployment_stage

Starts a stage in an edge deployment plan

sagemaker_list_trials

Lists the trials in your account

sagemaker_update_cluster_software

Updates the platform software of a SageMaker HyperPod cluster for security patching

sagemaker_update_mlflow_tracking_server

Updates properties of an existing MLflow Tracking Server

sagemaker_stop_transform_job

Stops a batch transform job

sagemaker_send_pipeline_execution_step_success

Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step's output parameters

sagemaker_stop_training_job

Stops a training job

sagemaker_update_inference_experiment

Updates an inference experiment that you created

sagemaker_list_resource_catalogs

Lists Amazon SageMaker Catalogs based on given filters and orders

sagemaker_list_lineage_groups

A list of lineage groups shared with your Amazon Web Services account

sagemaker_describe_hyper_parameter_tuning_job

Returns a description of a hyperparameter tuning job, depending on the fields selected

sagemaker_describe_optimization_job

Provides the properties of the specified optimization job

sagemaker_describe_image

Describes a SageMaker AI image

sagemaker_list_user_profiles

Lists user profiles

sagemaker_describe_model

Describes a model that you created using the CreateModel API

sagemaker_list_workteams

Gets a list of private work teams that you have defined in a region

sagemaker_describe_partner_app

Gets information about a SageMaker Partner AI App

sagemaker_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

sagemaker_list_experiments

Lists all the experiments in your account

sagemaker_stop_monitoring_schedule

Stops a previously started monitoring schedule

sagemaker_update_notebook_instance

Updates a notebook instance

sagemaker_update_partner_app

Updates all of the SageMaker Partner AI Apps in an account

sagemaker_update_hub

Update a hub

sagemaker_search

Finds SageMaker resources that match a search query

sagemaker_update_endpoint

Deploys the EndpointConfig specified in the request to a new fleet of instances

sagemaker_list_compute_quotas

List the resource allocation definitions

sagemaker_describe_pipeline_definition_for_execution

Describes the details of an execution's pipeline definition

sagemaker_import_hub_content

Import hub content

sagemaker_list_inference_components

Lists the inference components in your account and their properties

sagemaker_stop_inference_recommendations_job

Stops an Inference Recommender job

sagemaker_put_model_package_group_policy

Adds a resouce policy to control access to a model group

sagemaker_search_training_plan_offerings

Searches for available training plan offerings based on specified criteria

sagemaker_list_spaces

Lists spaces

sagemaker_update_context

Updates a context

sagemaker_update_notebook_instance_lifecycle_config

Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API

sagemaker_stop_labeling_job

Stops a running labeling job

sagemaker_list_domains

Lists the domains

sagemaker_update_inference_component_runtime_config

Runtime settings for a model that is deployed with an inference component

sagemakergeospatialcapabilities_delete_vector_enrichment_job

Use this operation to delete a Vector Enrichment job

sagemaker_update_device_fleet

Updates a fleet of devices

sagemaker_update_inference_component

Updates an inference component

sagemakergeospatialcapabilities_export_earth_observation_job

Use this operation to export results of an Earth Observation job and optionally source images used as input to the EOJ to an Amazon S3 location

sagemaker_list_flow_definitions

Returns information about the flow definitions in your account

sagemaker_update_pipeline

Updates a pipeline

sagemakerfeaturestoreruntime

Amazon SageMaker Feature Store Runtime

sagemaker_update_space

Updates the settings of a space

sagemaker_disable_sagemaker_servicecatalog_portfolio

Disables using Service Catalog in SageMaker

sagemaker_describe_subscribed_workteam

Gets information about a work team provided by a vendor

sagemaker_disassociate_trial_component

Disassociates a trial component from a trial

sagemakeredgemanager_send_heartbeat

Use to get the current status of devices registered on SageMaker Edge Manager

sagemaker_update_training_job

Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length

sagemaker_update_feature_metadata

Updates the description and parameters of the feature group

sagemaker_list_model_packages

Lists the model packages that have been created

sagemaker_list_aliases

Lists the aliases of a specified image or image version

sagemaker_list_model_package_groups

Gets a list of the model groups in your Amazon Web Services account

sagemaker_list_contexts

Lists the contexts in your account and their properties

sagemaker_update_workteam

Updates an existing work team with new member definitions or description

sagemaker_list_model_card_export_jobs

List the export jobs for the Amazon SageMaker Model Card

sagemakeredgemanager

Amazon Sagemaker Edge Manager

sagemakergeospatialcapabilities_get_tile

Gets a web mercator tile for the given Earth Observation job

sagemakergeospatialcapabilities_export_vector_enrichment_job

Use this operation to copy results of a Vector Enrichment job to an Amazon S3 location

sagemaker_update_experiment

Adds, updates, or removes the description of an experiment

sagemaker_list_inference_experiments

Returns the list of all inference experiments

sagemaker_list_monitoring_alert_history

Gets a list of past alerts in a model monitoring schedule

sagemakergeospatialcapabilities_stop_earth_observation_job

Use this operation to stop an existing earth observation job

sagemaker_query_lineage

Use this action to inspect your lineage and discover relationships between entities

sagemaker_list_processing_jobs

Lists processing jobs that satisfy various filters

sagemakergeospatialcapabilities_get_earth_observation_job

Get the details for a previously initiated Earth Observation job

sagemaker_list_feature_groups

List FeatureGroups based on given filter and order

sagemaker_start_notebook_instance

Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume

sagemakermetrics_batch_get_metrics

Used to retrieve training metrics from SageMaker

sagemakermetrics_batch_put_metrics

Used to ingest training metrics into SageMaker

sagemakerruntime_invoke_endpoint

After you deploy a model into production using Amazon SageMaker hosting services, your client applications use this API to get inferences from the model hosted at the specified endpoint

sagemakergeospatialcapabilities_stop_vector_enrichment_job

Stops the Vector Enrichment job for a given job ARN

sagemaker_list_monitoring_executions

Returns list of all monitoring job executions

sagemaker_list_associations

Lists the associations in your account and their properties

sagemaker_list_monitoring_alerts

Gets the alerts for a single monitoring schedule

sagemakergeospatialcapabilities_list_earth_observation_jobs

Use this operation to get a list of the Earth Observation jobs associated with the calling Amazon Web Services account

sagemakerruntime

Amazon SageMaker Runtime

textract_detect_document_text

Detects text in the input document

sagemakerruntime_invoke_endpoint_async

After you deploy a model into production using Amazon SageMaker hosting services, your client applications use this API to get inferences from the model hosted at the specified endpoint in an asynchronous manner

textract_delete_adapter_version

Deletes an Amazon Textract adapter version

textract_create_adapter_version

Creates a new version of an adapter

sagemaker_list_app_image_configs

Lists the AppImageConfigs in your account and their properties

sagemaker_render_ui_template

Renders the UI template so that you can preview the worker's experience

sagemaker_list_notebook_instance_lifecycle_configs

Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API

sagemaker_list_endpoints

Lists endpoints

sagemaker_list_endpoint_configs

Lists endpoint configurations

sagemaker_start_monitoring_schedule

Starts a previously stopped monitoring schedule

sagemaker_update_project

Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model

sagemakergeospatialcapabilities_list_vector_enrichment_jobs

Retrieves a list of vector enrichment jobs

sagemaker_list_training_jobs

Lists training jobs

sagemaker_list_mlflow_tracking_servers

Lists all MLflow Tracking Servers

sagemaker_list_hubs

List all existing hubs

sagemaker_list_monitoring_schedules

Returns list of all monitoring schedules

sagemaker_stop_compilation_job

Stops a model compilation job

textract_start_expense_analysis

Starts the asynchronous analysis of invoices or receipts for data like contact information, items purchased, and vendor names

sagemakerfeaturestoreruntime_batch_get_record

Retrieves a batch of Records from a FeatureGroup

sagemaker_retry_pipeline_execution

Retry the execution of the pipeline

textract_get_lending_analysis_summary

Gets summarized results for the StartLendingAnalysis operation, which analyzes text in a lending document

sagemaker_start_pipeline_execution

Starts a pipeline execution

textract_delete_adapter

Deletes an Amazon Textract adapter

sagemakerfeaturestoreruntime_delete_record

Deletes a Record from a FeatureGroup in the OnlineStore

sagemaker_stop_optimization_job

Ends a running inference optimization job

textract_list_adapter_versions

List all version of an adapter that meet the specified filtration criteria

textract_start_lending_analysis

Starts the classification and analysis of an input document

sagemaker_update_monitoring_alert

Update the parameters of a model monitor alert

transcribeservice_create_medical_vocabulary

Creates a new custom medical vocabulary

transcribeservice_get_call_analytics_job

Provides information about the specified Call Analytics job

transcribeservice_create_vocabulary

Creates a new custom vocabulary

transcribeservice_get_medical_scribe_job

Provides information about the specified Medical Scribe job

textract_tag_resource

Adds one or more tags to the specified resource

sagemaker_update_trial_component

Updates one or more properties of a trial component

textract_get_adapter_version

Gets configuration information for the specified adapter version, including: AdapterId, AdapterVersion, FeatureTypes, Status, StatusMessage, DatasetConfig, KMSKeyId, OutputConfig, Tags and EvaluationMetrics

sagemaker_list_notebook_instances

Returns a list of the SageMaker AI notebook instances in the requester's account in an Amazon Web Services Region

sagemaker_stop_edge_packaging_job

Request to stop an edge packaging job

sagemaker_list_pipeline_execution_steps

Gets a list of PipeLineExecutionStep objects

sagemaker_list_pipeline_executions

Gets a list of the pipeline executions

transcribeservice_list_medical_vocabularies

Provides a list of custom medical vocabularies that match the specified criteria

transcribeservice_list_tags_for_resource

Lists all tags associated with the specified transcription job, vocabulary, model, or resource

sagemakermetrics

Amazon SageMaker Metrics Service

sagemakergeospatialcapabilities_list_raster_data_collections

Use this operation to get raster data collections

sagemakerruntime_invoke_endpoint_with_response_stream

Invokes a model at the specified endpoint to return the inference response as a stream

sagemakergeospatialcapabilities_list_tags_for_resource

Lists the tags attached to the resource

textract_list_tags_for_resource

Lists all tags for an Amazon Textract resource

textract_list_adapters

Lists all adapters that match the specified filtration criteria

textract

Amazon Textract

transcribeservice_delete_language_model

Deletes a custom language model

transcribeservice_delete_call_analytics_job

Deletes a Call Analytics job

transcribeservice_delete_vocabulary

Deletes a custom vocabulary

sagemaker_update_action

Updates an action

textract_untag_resource

Removes any tags with the specified keys from the specified resource

transcribeservice_delete_transcription_job

Deletes a transcription job

transcribeservice_get_vocabulary

Provides information about the specified custom vocabulary

sagemaker_stop_edge_deployment_stage

Stops a stage in an edge deployment plan

transcribeservice_get_transcription_job

Provides information about the specified transcription job

transcribeservice_update_medical_vocabulary

Updates an existing custom medical vocabulary with new values

transcribeservice_update_vocabulary

Updates an existing custom vocabulary with new values

transcribeservice_delete_vocabulary_filter

Deletes a custom vocabulary filter

sagemaker_update_code_repository

Updates the specified Git repository with the specified values

textract_get_adapter

Gets configuration information for an adapter specified by an AdapterId, returning information on AdapterName, Description, CreationTime, AutoUpdate status, and FeatureTypes

sagemaker_update_compute_quota

Update the compute allocation definition

sagemakergeospatialcapabilities_delete_earth_observation_job

Use this operation to delete an Earth Observation job

transcribeservice_list_medical_transcription_jobs

Provides a list of medical transcription jobs that match the specified criteria

translate_get_parallel_data

Provides information about a parallel data resource

transcribeservice_list_vocabulary_filters

Provides a list of custom vocabulary filters that match the specified criteria

sagemaker_update_app_image_config

Updates the properties of an AppImageConfig

transcribeservice

Amazon Transcribe Service

sagemaker_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

sagemaker_register_devices

Register devices

sagemakerfeaturestoreruntime_get_record

Use for OnlineStore serving from a FeatureStore

sagemakeredgemanager_get_deployments

Use to get the active deployments from a device

translate_list_parallel_data

Provides a list of your parallel data resources in Amazon Translate

sagemaker_update_image_version

Updates the properties of a SageMaker AI image version

sagemaker_update_devices

Updates one or more devices in a fleet

sagemaker_list_workforces

Use this operation to list all private and vendor workforces in an Amazon Web Services Region

sagemaker_stop_notebook_instance

Terminates the ML compute instance

sagemaker_start_inference_experiment

Starts an inference experiment

sagemaker_stop_processing_job

Stops a processing job

sagemaker_update_image

Updates the properties of a SageMaker AI image

translate_delete_parallel_data

Deletes a parallel data resource in Amazon Translate

sagemaker_update_model_package

Updates a versioned model

sagemaker_update_user_profile

Updates a user profile

sagemaker_update_feature_group

Updates the feature group by either adding features or updating the online store configuration

translate_list_tags_for_resource

Lists all tags associated with a given Amazon Translate resource

translate_create_parallel_data

Creates a parallel data resource in Amazon Translate by importing an input file from Amazon S3

translate_list_languages

Provides a list of languages (RFC-5646 codes and names) that Amazon Translate supports

transcribeservice_delete_medical_vocabulary

Deletes a custom medical vocabulary

translate_import_terminology

Creates or updates a custom terminology, depending on whether one already exists for the given terminology name

translate_untag_resource

Removes a specific tag associated with an Amazon Translate resource

transcribeservice_start_call_analytics_job

Transcribes the audio from a customer service call and applies any additional Request Parameters you choose to include in your request

translate_translate_text

Translates input text from the source language to the target language

sagemakergeospatialcapabilities_start_earth_observation_job

Use this operation to create an Earth observation job

sagemaker_update_monitoring_schedule

Updates a previously created schedule

voiceid_delete_fraudster

Deletes the specified fraudster from Voice ID

voiceid_describe_speaker

Describes the specified speaker

voiceid_describe_speaker_enrollment_job

Describes the specified speaker enrollment job

voiceid_delete_speaker

Deletes the specified speaker from Voice ID

transcribeservice_delete_call_analytics_category

Deletes a Call Analytics category

sagemaker_stop_pipeline_execution

Stops a pipeline execution

sagemakeredgemanager_get_device_registration

Use to check if a device is registered with SageMaker Edge Manager

sagemaker_update_model_card

Update an Amazon SageMaker Model Card

transcribeservice_list_medical_scribe_jobs

Provides a list of Medical Scribe jobs that match the specified criteria

sagemakergeospatialcapabilities_start_vector_enrichment_job

Creates a Vector Enrichment job for the supplied job type

sagemaker_update_domain

Updates the default settings for new user profiles in the domain

sagemakergeospatialcapabilities

Amazon SageMaker geospatial capabilities

sagemaker_update_trial

Updates the display name of a trial

voiceid_create_watchlist

Creates a watchlist that fraudsters can be a part of

voiceid_describe_fraudster_registration_job

Describes the specified fraudster registration job

voiceid_untag_resource

Removes specified tags from a specified Amazon Connect Voice ID resource

voiceid_start_speaker_enrollment_job

Starts a new batch speaker enrollment job using specified details

textract_analyze_document

Analyzes an input document for relationships between detected items

voiceid_tag_resource

Tags a Voice ID resource with the provided list of tags

textract_start_document_analysis

Starts the asynchronous analysis of an input document for relationships between detected items such as key-value pairs, tables, and selection elements

textract_get_document_analysis

Gets the results for an Amazon Textract asynchronous operation that analyzes text in a document

transcribeservice_describe_language_model

Provides information about the specified custom language model

voiceid_update_domain

Updates the specified domain

transcribeservice_list_transcription_jobs

Provides a list of transcription jobs that match the specified criteria

sagemakergeospatialcapabilities_get_vector_enrichment_job

Retrieves details of a Vector Enrichment Job for a given job Amazon Resource Name (ARN)

sagemakerfeaturestoreruntime_put_record

The PutRecord API is used to ingest a list of Records into your feature group

transcribeservice_get_call_analytics_category

Provides information about the specified Call Analytics category

textract_update_adapter

Update the configuration for an adapter

transcribeservice_list_call_analytics_jobs

Provides a list of Call Analytics jobs that match the specified criteria

transcribeservice_start_medical_scribe_job

Transcribes patient-clinician conversations and generates clinical notes

sagemakergeospatialcapabilities_get_raster_data_collection

Use this operation to get details of a specific raster data collection

sagemaker_update_workforce

Use this operation to update your workforce

sagemakergeospatialcapabilities_tag_resource

The resource you want to tag

sagemakergeospatialcapabilities_untag_resource

The resource you want to untag

textract_get_expense_analysis

Gets the results for an Amazon Textract asynchronous operation that analyzes invoices and receipts

voiceid_list_speaker_enrollment_jobs

Lists all the speaker enrollment jobs in the domain with the specified JobStatus

translate_get_terminology

Retrieves a custom terminology

textract_analyze_expense

AnalyzeExpense synchronously analyzes an input document for financially related relationships between text

voiceid_list_speakers

Lists all speakers in a specified domain

textract_get_document_text_detection

Gets the results for an Amazon Textract asynchronous operation that detects text in a document

transcribeservice_list_vocabularies

Provides a list of custom vocabularies that match the specified criteria

transcribeservice_delete_medical_scribe_job

Deletes a Medical Scribe job

textract_create_adapter

Creates an adapter, which can be fine-tuned for enhanced performance on user provided documents

textract_analyze_id

Analyzes identity documents for relevant information

voiceid_update_watchlist

Updates the specified watchlist

transcribeservice_create_call_analytics_category

Creates a new Call Analytics category

transcribeservice_start_transcription_job

Transcribes the audio from a media file and applies any additional Request Parameters you choose to include in your request

transcribeservice_delete_medical_transcription_job

Deletes a medical transcription job

textract_get_lending_analysis

Gets the results for an Amazon Textract asynchronous operation that analyzes text in a lending document

transcribeservice_get_medical_transcription_job

Provides information about the specified medical transcription job

transcribeservice_create_language_model

Creates a new custom language model

transcribeservice_create_vocabulary_filter

Creates a new custom vocabulary filter

voiceid

Amazon Voice ID

sagemakergeospatialcapabilities_search_raster_data_collection

Allows you run image query on a specific raster data collection to get a list of the satellite imagery matching the selected filters

sagemaker_update_pipeline_execution

Updates a pipeline execution

transcribeservice_list_language_models

Provides a list of custom language models that match the specified criteria

voiceid_describe_domain

Describes the specified domain

translate

Amazon Translate

transcribeservice_update_vocabulary_filter

Updates an existing custom vocabulary filter with a new list of words

voiceid_describe_fraudster

Describes the specified fraudster

voiceid_delete_domain

Deletes the specified domain from Voice ID

translate_list_text_translation_jobs

Gets a list of the batch translation jobs that you have submitted

translate_list_terminologies

Provides a list of custom terminologies associated with your account

transcribeservice_start_medical_transcription_job

Transcribes the audio from a medical dictation or conversation and applies any additional Request Parameters you choose to include in your request

transcribeservice_get_vocabulary_filter

Provides information about the specified custom vocabulary filter

transcribeservice_list_call_analytics_categories

Provides a list of Call Analytics categories, including all rules that make up each category

voiceid_associate_fraudster

Associates the fraudsters with the watchlist specified in the same domain

voiceid_opt_out_speaker

Opts out a speaker from Voice ID

transcribeservice_untag_resource

Removes the specified tags from the specified Amazon Transcribe resource

translate_update_parallel_data

Updates a previously created parallel data resource by importing a new input file from Amazon S3

voiceid_delete_watchlist

Deletes the specified watchlist from Voice ID

translate_describe_text_translation_job

Gets the properties associated with an asynchronous batch translation job including name, ID, status, source and target languages, input/output S3 buckets, and so on

textract_start_document_text_detection

Starts the asynchronous detection of text in a document

transcribeservice_tag_resource

Adds one or more custom tags, each in the form of a key:value pair, to the specified resource

voiceid_list_tags_for_resource

Lists all tags associated with a specified Voice ID resource

translate_tag_resource

Associates a specific tag with a resource

voiceid_start_fraudster_registration_job

Starts a new batch fraudster registration job using provided details

transcribeservice_update_call_analytics_category

Updates the specified Call Analytics category with new rules

transcribeservice_get_medical_vocabulary

Provides information about the specified custom medical vocabulary

voiceid_evaluate_session

Evaluates a specified session based on audio data accumulated during a streaming Amazon Connect Voice ID call

translate_start_text_translation_job

Starts an asynchronous batch translation job

translate_stop_text_translation_job

Stops an asynchronous batch translation job that is in progress

translate_delete_terminology

A synchronous action that deletes a custom terminology

voiceid_list_domains

Lists all the domains in the Amazon Web Services account

voiceid_list_fraudsters

Lists all fraudsters in a specified watchlist or domain

translate_translate_document

Translates the input document from the source language to the target language

voiceid_list_fraudster_registration_jobs

Lists all the fraudster registration jobs in the domain with the given JobStatus

voiceid_describe_watchlist

Describes the specified watchlist

voiceid_create_domain

Creates a domain that contains all Amazon Connect Voice ID data, such as speakers, fraudsters, customer audio, and voiceprints

voiceid_list_watchlists

Lists all watchlists in a specified domain

voiceid_disassociate_fraudster

Disassociates the fraudsters from the watchlist specified

paws.machine.learning (version 0.9.0)

'Amazon Web Services' Machine Learning Services

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Functions in paws.machine.learning (0.9.0)