Literals#
Index > MachineLearning > Literals
Auto-generated documentation for MachineLearning type annotations stubs module types-boto3-machinelearning.
AlgorithmType#
# AlgorithmType usage example
from types_boto3_machinelearning.literals import AlgorithmType
def get_value() -> AlgorithmType:
return "sgd"
# AlgorithmType definition
AlgorithmType = Literal[
"sgd",
]
BatchPredictionAvailableWaiterName#
# BatchPredictionAvailableWaiterName usage example
from types_boto3_machinelearning.literals import BatchPredictionAvailableWaiterName
def get_value() -> BatchPredictionAvailableWaiterName:
return "batch_prediction_available"
# BatchPredictionAvailableWaiterName definition
BatchPredictionAvailableWaiterName = Literal[
"batch_prediction_available",
]
BatchPredictionFilterVariableType#
# BatchPredictionFilterVariableType usage example
from types_boto3_machinelearning.literals import BatchPredictionFilterVariableType
def get_value() -> BatchPredictionFilterVariableType:
return "CreatedAt"
# BatchPredictionFilterVariableType definition
BatchPredictionFilterVariableType = Literal[
"CreatedAt",
"DataSourceId",
"DataURI",
"IAMUser",
"LastUpdatedAt",
"MLModelId",
"Name",
"Status",
]
DataSourceAvailableWaiterName#
# DataSourceAvailableWaiterName usage example
from types_boto3_machinelearning.literals import DataSourceAvailableWaiterName
def get_value() -> DataSourceAvailableWaiterName:
return "data_source_available"
# DataSourceAvailableWaiterName definition
DataSourceAvailableWaiterName = Literal[
"data_source_available",
]
DataSourceFilterVariableType#
# DataSourceFilterVariableType usage example
from types_boto3_machinelearning.literals import DataSourceFilterVariableType
def get_value() -> DataSourceFilterVariableType:
return "CreatedAt"
# DataSourceFilterVariableType definition
DataSourceFilterVariableType = Literal[
"CreatedAt",
"DataLocationS3",
"IAMUser",
"LastUpdatedAt",
"Name",
"Status",
]
DescribeBatchPredictionsPaginatorName#
# DescribeBatchPredictionsPaginatorName usage example
from types_boto3_machinelearning.literals import DescribeBatchPredictionsPaginatorName
def get_value() -> DescribeBatchPredictionsPaginatorName:
return "describe_batch_predictions"
# DescribeBatchPredictionsPaginatorName definition
DescribeBatchPredictionsPaginatorName = Literal[
"describe_batch_predictions",
]
DescribeDataSourcesPaginatorName#
# DescribeDataSourcesPaginatorName usage example
from types_boto3_machinelearning.literals import DescribeDataSourcesPaginatorName
def get_value() -> DescribeDataSourcesPaginatorName:
return "describe_data_sources"
# DescribeDataSourcesPaginatorName definition
DescribeDataSourcesPaginatorName = Literal[
"describe_data_sources",
]
DescribeEvaluationsPaginatorName#
# DescribeEvaluationsPaginatorName usage example
from types_boto3_machinelearning.literals import DescribeEvaluationsPaginatorName
def get_value() -> DescribeEvaluationsPaginatorName:
return "describe_evaluations"
# DescribeEvaluationsPaginatorName definition
DescribeEvaluationsPaginatorName = Literal[
"describe_evaluations",
]
DescribeMLModelsPaginatorName#
# DescribeMLModelsPaginatorName usage example
from types_boto3_machinelearning.literals import DescribeMLModelsPaginatorName
def get_value() -> DescribeMLModelsPaginatorName:
return "describe_ml_models"
# DescribeMLModelsPaginatorName definition
DescribeMLModelsPaginatorName = Literal[
"describe_ml_models",
]
DetailsAttributesType#
# DetailsAttributesType usage example
from types_boto3_machinelearning.literals import DetailsAttributesType
def get_value() -> DetailsAttributesType:
return "Algorithm"
# DetailsAttributesType definition
DetailsAttributesType = Literal[
"Algorithm",
"PredictiveModelType",
]
EntityStatusType#
# EntityStatusType usage example
from types_boto3_machinelearning.literals import EntityStatusType
def get_value() -> EntityStatusType:
return "COMPLETED"
# EntityStatusType definition
EntityStatusType = Literal[
"COMPLETED",
"DELETED",
"FAILED",
"INPROGRESS",
"PENDING",
]
EvaluationAvailableWaiterName#
# EvaluationAvailableWaiterName usage example
from types_boto3_machinelearning.literals import EvaluationAvailableWaiterName
def get_value() -> EvaluationAvailableWaiterName:
return "evaluation_available"
# EvaluationAvailableWaiterName definition
EvaluationAvailableWaiterName = Literal[
"evaluation_available",
]
EvaluationFilterVariableType#
# EvaluationFilterVariableType usage example
from types_boto3_machinelearning.literals import EvaluationFilterVariableType
def get_value() -> EvaluationFilterVariableType:
return "CreatedAt"
# EvaluationFilterVariableType definition
EvaluationFilterVariableType = Literal[
"CreatedAt",
"DataSourceId",
"DataURI",
"IAMUser",
"LastUpdatedAt",
"MLModelId",
"Name",
"Status",
]
MLModelAvailableWaiterName#
# MLModelAvailableWaiterName usage example
from types_boto3_machinelearning.literals import MLModelAvailableWaiterName
def get_value() -> MLModelAvailableWaiterName:
return "ml_model_available"
# MLModelAvailableWaiterName definition
MLModelAvailableWaiterName = Literal[
"ml_model_available",
]
MLModelFilterVariableType#
# MLModelFilterVariableType usage example
from types_boto3_machinelearning.literals import MLModelFilterVariableType
def get_value() -> MLModelFilterVariableType:
return "Algorithm"
# MLModelFilterVariableType definition
MLModelFilterVariableType = Literal[
"Algorithm",
"CreatedAt",
"IAMUser",
"LastUpdatedAt",
"MLModelType",
"Name",
"RealtimeEndpointStatus",
"Status",
"TrainingDataSourceId",
"TrainingDataURI",
]
MLModelTypeType#
# MLModelTypeType usage example
from types_boto3_machinelearning.literals import MLModelTypeType
def get_value() -> MLModelTypeType:
return "BINARY"
# MLModelTypeType definition
MLModelTypeType = Literal[
"BINARY",
"MULTICLASS",
"REGRESSION",
]
RealtimeEndpointStatusType#
# RealtimeEndpointStatusType usage example
from types_boto3_machinelearning.literals import RealtimeEndpointStatusType
def get_value() -> RealtimeEndpointStatusType:
return "FAILED"
# RealtimeEndpointStatusType definition
RealtimeEndpointStatusType = Literal[
"FAILED",
"NONE",
"READY",
"UPDATING",
]
SortOrderType#
# SortOrderType usage example
from types_boto3_machinelearning.literals import SortOrderType
def get_value() -> SortOrderType:
return "asc"
# SortOrderType definition
SortOrderType = Literal[
"asc",
"dsc",
]
TaggableResourceTypeType#
# TaggableResourceTypeType usage example
from types_boto3_machinelearning.literals import TaggableResourceTypeType
def get_value() -> TaggableResourceTypeType:
return "BatchPrediction"
# TaggableResourceTypeType definition
TaggableResourceTypeType = Literal[
"BatchPrediction",
"DataSource",
"Evaluation",
"MLModel",
]
MachineLearningServiceName#
# MachineLearningServiceName usage example
from types_boto3_machinelearning.literals import MachineLearningServiceName
def get_value() -> MachineLearningServiceName:
return "machinelearning"
# MachineLearningServiceName definition
MachineLearningServiceName = Literal[
"machinelearning",
]
ServiceName#
# ServiceName usage example
from types_boto3_machinelearning.literals import ServiceName
def get_value() -> ServiceName:
return "accessanalyzer"
# ServiceName definition
ServiceName = Literal[
"accessanalyzer",
"account",
"acm",
"acm-pca",
"amp",
"amplify",
"amplifybackend",
"amplifyuibuilder",
"apigateway",
"apigatewaymanagementapi",
"apigatewayv2",
"appconfig",
"appconfigdata",
"appfabric",
"appflow",
"appintegrations",
"application-autoscaling",
"application-insights",
"application-signals",
"applicationcostprofiler",
"appmesh",
"apprunner",
"appstream",
"appsync",
"apptest",
"arc-zonal-shift",
"artifact",
"athena",
"auditmanager",
"autoscaling",
"autoscaling-plans",
"b2bi",
"backup",
"backup-gateway",
"backupsearch",
"batch",
"bcm-data-exports",
"bcm-pricing-calculator",
"bedrock",
"bedrock-agent",
"bedrock-agent-runtime",
"bedrock-data-automation",
"bedrock-data-automation-runtime",
"bedrock-runtime",
"billing",
"billingconductor",
"braket",
"budgets",
"ce",
"chatbot",
"chime",
"chime-sdk-identity",
"chime-sdk-media-pipelines",
"chime-sdk-meetings",
"chime-sdk-messaging",
"chime-sdk-voice",
"cleanrooms",
"cleanroomsml",
"cloud9",
"cloudcontrol",
"clouddirectory",
"cloudformation",
"cloudfront",
"cloudfront-keyvaluestore",
"cloudhsm",
"cloudhsmv2",
"cloudsearch",
"cloudsearchdomain",
"cloudtrail",
"cloudtrail-data",
"cloudwatch",
"codeartifact",
"codebuild",
"codecatalyst",
"codecommit",
"codeconnections",
"codedeploy",
"codeguru-reviewer",
"codeguru-security",
"codeguruprofiler",
"codepipeline",
"codestar-connections",
"codestar-notifications",
"cognito-identity",
"cognito-idp",
"cognito-sync",
"comprehend",
"comprehendmedical",
"compute-optimizer",
"config",
"connect",
"connect-contact-lens",
"connectcampaigns",
"connectcampaignsv2",
"connectcases",
"connectparticipant",
"controlcatalog",
"controltower",
"cost-optimization-hub",
"cur",
"customer-profiles",
"databrew",
"dataexchange",
"datapipeline",
"datasync",
"datazone",
"dax",
"deadline",
"detective",
"devicefarm",
"devops-guru",
"directconnect",
"discovery",
"dlm",
"dms",
"docdb",
"docdb-elastic",
"drs",
"ds",
"ds-data",
"dsql",
"dynamodb",
"dynamodbstreams",
"ebs",
"ec2",
"ec2-instance-connect",
"ecr",
"ecr-public",
"ecs",
"efs",
"eks",
"eks-auth",
"elastic-inference",
"elasticache",
"elasticbeanstalk",
"elastictranscoder",
"elb",
"elbv2",
"emr",
"emr-containers",
"emr-serverless",
"entityresolution",
"es",
"events",
"evidently",
"finspace",
"finspace-data",
"firehose",
"fis",
"fms",
"forecast",
"forecastquery",
"frauddetector",
"freetier",
"fsx",
"gamelift",
"geo-maps",
"geo-places",
"geo-routes",
"glacier",
"globalaccelerator",
"glue",
"grafana",
"greengrass",
"greengrassv2",
"groundstation",
"guardduty",
"health",
"healthlake",
"iam",
"identitystore",
"imagebuilder",
"importexport",
"inspector",
"inspector-scan",
"inspector2",
"internetmonitor",
"invoicing",
"iot",
"iot-data",
"iot-jobs-data",
"iot1click-devices",
"iot1click-projects",
"iotanalytics",
"iotdeviceadvisor",
"iotevents",
"iotevents-data",
"iotfleethub",
"iotfleetwise",
"iotsecuretunneling",
"iotsitewise",
"iotthingsgraph",
"iottwinmaker",
"iotwireless",
"ivs",
"ivs-realtime",
"ivschat",
"kafka",
"kafkaconnect",
"kendra",
"kendra-ranking",
"keyspaces",
"kinesis",
"kinesis-video-archived-media",
"kinesis-video-media",
"kinesis-video-signaling",
"kinesis-video-webrtc-storage",
"kinesisanalytics",
"kinesisanalyticsv2",
"kinesisvideo",
"kms",
"lakeformation",
"lambda",
"launch-wizard",
"lex-models",
"lex-runtime",
"lexv2-models",
"lexv2-runtime",
"license-manager",
"license-manager-linux-subscriptions",
"license-manager-user-subscriptions",
"lightsail",
"location",
"logs",
"lookoutequipment",
"lookoutmetrics",
"lookoutvision",
"m2",
"machinelearning",
"macie2",
"mailmanager",
"managedblockchain",
"managedblockchain-query",
"marketplace-agreement",
"marketplace-catalog",
"marketplace-deployment",
"marketplace-entitlement",
"marketplace-reporting",
"marketplacecommerceanalytics",
"mediaconnect",
"mediaconvert",
"medialive",
"mediapackage",
"mediapackage-vod",
"mediapackagev2",
"mediastore",
"mediastore-data",
"mediatailor",
"medical-imaging",
"memorydb",
"meteringmarketplace",
"mgh",
"mgn",
"migration-hub-refactor-spaces",
"migrationhub-config",
"migrationhuborchestrator",
"migrationhubstrategy",
"mq",
"mturk",
"mwaa",
"neptune",
"neptune-graph",
"neptunedata",
"network-firewall",
"networkflowmonitor",
"networkmanager",
"networkmonitor",
"notifications",
"notificationscontacts",
"oam",
"observabilityadmin",
"omics",
"opensearch",
"opensearchserverless",
"opsworks",
"opsworkscm",
"organizations",
"osis",
"outposts",
"panorama",
"partnercentral-selling",
"payment-cryptography",
"payment-cryptography-data",
"pca-connector-ad",
"pca-connector-scep",
"pcs",
"personalize",
"personalize-events",
"personalize-runtime",
"pi",
"pinpoint",
"pinpoint-email",
"pinpoint-sms-voice",
"pinpoint-sms-voice-v2",
"pipes",
"polly",
"pricing",
"privatenetworks",
"proton",
"qapps",
"qbusiness",
"qconnect",
"qldb",
"qldb-session",
"quicksight",
"ram",
"rbin",
"rds",
"rds-data",
"redshift",
"redshift-data",
"redshift-serverless",
"rekognition",
"repostspace",
"resiliencehub",
"resource-explorer-2",
"resource-groups",
"resourcegroupstaggingapi",
"robomaker",
"rolesanywhere",
"route53",
"route53-recovery-cluster",
"route53-recovery-control-config",
"route53-recovery-readiness",
"route53domains",
"route53profiles",
"route53resolver",
"rum",
"s3",
"s3control",
"s3outposts",
"s3tables",
"sagemaker",
"sagemaker-a2i-runtime",
"sagemaker-edge",
"sagemaker-featurestore-runtime",
"sagemaker-geospatial",
"sagemaker-metrics",
"sagemaker-runtime",
"savingsplans",
"scheduler",
"schemas",
"sdb",
"secretsmanager",
"security-ir",
"securityhub",
"securitylake",
"serverlessrepo",
"service-quotas",
"servicecatalog",
"servicecatalog-appregistry",
"servicediscovery",
"ses",
"sesv2",
"shield",
"signer",
"simspaceweaver",
"sms",
"sms-voice",
"snow-device-management",
"snowball",
"sns",
"socialmessaging",
"sqs",
"ssm",
"ssm-contacts",
"ssm-incidents",
"ssm-quicksetup",
"ssm-sap",
"sso",
"sso-admin",
"sso-oidc",
"stepfunctions",
"storagegateway",
"sts",
"supplychain",
"support",
"support-app",
"swf",
"synthetics",
"taxsettings",
"textract",
"timestream-influxdb",
"timestream-query",
"timestream-write",
"tnb",
"transcribe",
"transfer",
"translate",
"trustedadvisor",
"verifiedpermissions",
"voice-id",
"vpc-lattice",
"waf",
"waf-regional",
"wafv2",
"wellarchitected",
"wisdom",
"workdocs",
"workmail",
"workmailmessageflow",
"workspaces",
"workspaces-thin-client",
"workspaces-web",
"xray",
]
ResourceServiceName#
# ResourceServiceName usage example
from types_boto3_machinelearning.literals import ResourceServiceName
def get_value() -> ResourceServiceName:
return "cloudformation"
# ResourceServiceName definition
ResourceServiceName = Literal[
"cloudformation",
"cloudwatch",
"dynamodb",
"ec2",
"glacier",
"iam",
"opsworks",
"s3",
"sns",
"sqs",
]
PaginatorName#
# PaginatorName usage example
from types_boto3_machinelearning.literals import PaginatorName
def get_value() -> PaginatorName:
return "describe_batch_predictions"
# PaginatorName definition
PaginatorName = Literal[
"describe_batch_predictions",
"describe_data_sources",
"describe_evaluations",
"describe_ml_models",
]
WaiterName#
# WaiterName usage example
from types_boto3_machinelearning.literals import WaiterName
def get_value() -> WaiterName:
return "batch_prediction_available"
# WaiterName definition
WaiterName = Literal[
"batch_prediction_available",
"data_source_available",
"evaluation_available",
"ml_model_available",
]
RegionName#
# RegionName usage example
from types_boto3_machinelearning.literals import RegionName
def get_value() -> RegionName:
return "eu-west-1"
# RegionName definition
RegionName = Literal[
"eu-west-1",
"us-east-1",
]