The name of the inference scheduler to be started.

Indicates the status of the inference scheduler.

The Amazon Resource Name (ARN) of the ML model being used by the inference scheduler.

The name of the ML model being used by the inference scheduler.

The Amazon Resource Name (ARN) of the inference scheduler being started.

The name of the inference scheduler being started.

The response's http status code.

The name of the dataset to be described.

Specifies the S3 location configuration for the data input for the data ingestion job.

Indicates the status of the dataset.

The Amazon Resource Name (ARN) of the dataset being described.

Specifies the time the dataset was last updated, if it was.

Specifies the time the dataset was created in Amazon Lookout for Equipment.

A JSON description of the data that is in each time series dataset, including names, column names, and data types.

The name of the dataset being described.

Provides the identifier of the KMS key used to encrypt dataset data by Amazon Lookout for Equipment.

The response's http status code.

The Amazon Resource Name (ARN) of the resource (such as the dataset or model) that is the focus of the ListTagsForResource operation.

Any tags associated with the resource.

The response's http status code.

The job ID of the data ingestion job.

Specifies the S3 location configuration for the data input for the data ingestion job.

Indicates the status of the DataIngestionJob operation.

The Amazon Resource Name (ARN) of the dataset being used in the data ingestion job.

Specifies the reason for failure when a data ingestion job has failed.

Indicates the job ID of the data ingestion job.

The time at which the data ingestion job was created.

The Amazon Resource Name (ARN) of an IAM role with permission to access the data source being ingested.

The response's http status code.

The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.

When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H

Indicates the time reference in the dataset that should be used to end the subset of training data for the ML model.

The data schema for the ML model being created.

Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the ML model.

Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.

Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the ML model.

Indicates the time reference in the dataset that should be used to begin the subset of training data for the ML model.

The input configuration for the labels being used for the ML model that's being created.

Any tags associated with the ML model being created.

Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.

The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the ML model.

The name for the ML model to be created.

The name of the dataset for the ML model being created.

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

Indicates the status of the CreateModel operation.

The Amazon Resource Name (ARN) of the model being created.

The response's http status code.

The name of the dataset to be deleted.

Any tags associated with the ingested data described in the dataset.

Provides the identifier of the KMS key used to encrypt dataset data by Amazon Lookout for Equipment.

The name of the dataset being created.

A JSON description of the data that is in each time series dataset, including names, column names, and data types.

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

Indicates the status of the CreateDataset operation.

The Amazon Resource Name (ARN) of the dataset being created.

The name of the dataset being created.

The response's http status code.

The name of the ML model to be deleted.

The status of the ML model.

An opaque pagination token indicating where to continue the listing of ML models.

The beginning of the name of the dataset of the ML models to be listed.

The beginning of the name of the ML models being listed.

Specifies the maximum number of ML models to list.

An opaque pagination token indicating where to continue the listing of ML models.

Provides information on the specified model, including created time, model and dataset ARNs, and status.

The response's http status code.

The name of the inference scheduler to be stopped.

Indicates the status of the inference scheduler.

The Amazon Resource Name (ARN) of the ML model used by the inference scheduler being stopped.

The name of the ML model used by the inference scheduler being stopped.

The Amazon Resource Name (ARN) of the inference schedule being stopped.

The name of the inference scheduler being stopped.

The response's http status code.

Indicates the status of the data ingestion job.

An opaque pagination token indicating where to continue the listing of data ingestion jobs.

The name of the dataset being used for the data ingestion job.

Specifies the maximum number of data ingestion jobs to list.

An opaque pagination token indicating where to continue the listing of data ingestion jobs.

Specifies information about the specific data ingestion job, including dataset name and status.

The response's http status code.

The name of the ML model to be described.

Specifies the current status of the model being described. Status describes the status of the most recent action of the model.

The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.

When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H

Indicates the time at which the training of the ML model began.

The Amazon Resouce Name (ARN) of the dataset used to create the ML model being described.

If the training of the ML model failed, this indicates the reason for that failure.

The Amazon Resource Name (ARN) of the ML model being described.

Indicates the last time the ML model was updated. The type of update is not specified.

Indicates the time reference in the dataset that was used to end the subset of training data for the ML model.

Indicates the time and date at which the ML model was created.

The name of the ML model being described.

The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.

Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML model.

A JSON description of the data that is in each time series dataset, including names, column names, and data types.

Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.

Indicates the time reference in the dataset that was used to end the subset of evaluation data for the ML model.

The name of the dataset being used by the ML being described.

Indicates the time reference in the dataset that was used to begin the subset of training data for the ML model.

Indicates the time at which the training of the ML model was completed.

Specifies configuration information about the labels input, including its S3 location.

Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.

The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML model being described.

The response's http status code.

The name of the dataset being used by the data ingestion job.

Specifies information for the input data for the data ingestion job, including dataset S3 location.

The Amazon Resource Name (ARN) of a role with permission to access the data source for the data ingestion job.

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

Indicates the status of the StartDataIngestionJob operation.

Indicates the job ID of the data ingestion job.

The response's http status code.

The name of the ML model used by the inference scheduler to be listed.

An opaque pagination token indicating where to continue the listing of inference schedulers.

The beginning of the name of the inference schedulers to be listed.

Specifies the maximum number of inference schedulers to list.

Provides information about the specified inference scheduler, including data upload frequency, model name and ARN, and status.

An opaque pagination token indicating where to continue the listing of inference schedulers.

The response's http status code.

How often data is uploaded to the source S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if you select an offset delay time of five minutes, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don't need to stop and restart the scheduler when uploading new data.

Specifies information for the output results from the inference scheduler, including the output S3 location.

Specifies information for the input data for the inference scheduler, including delimiter, format, and dataset location.

The Amazon Resource Name (ARN) of a role with permission to access the data source for the inference scheduler.

The name of the inference scheduler to be updated.

The name of the inference scheduler to be deleted.

The Amazon Resource Name (ARN) of the specific resource to which the tag should be associated.

The tag or tags to be associated with a specific resource. Both the tag key and value are specified.

The response's http status code.

The status of the inference execution.

The time reference in the inferenced dataset before which Amazon Lookout for Equipment stopped the inference execution.

An opaque pagination token indicating where to continue the listing of inference executions.

Specifies the maximum number of inference executions to list.

The time reference in the inferenced dataset after which Amazon Lookout for Equipment started the inference execution.

The name of the inference scheduler for the inference execution listed.

An opaque pagination token indicating where to continue the listing of inference executions.

Provides an array of information about the individual inference executions returned from the ListInferenceExecutions operation, including model used, inference scheduler, data configuration, and so on.

The response's http status code.

A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if you select an offset delay time of five minutes, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don't need to stop and restart the scheduler when uploading new data.

Any tags associated with the inference scheduler.

Provides the identifier of the KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment.

The name of the previously trained ML model being used to create the inference scheduler.

The name of the inference scheduler being created.

How often data is uploaded to the source S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

Specifies configuration information for the output results for the inference scheduler, including the S3 location for the output.

The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference.

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

Indicates the status of the CreateInferenceScheduler operation.

The Amazon Resource Name (ARN) of the inference scheduler being created.

The name of inference scheduler being created.

The response's http status code.

An opaque pagination token indicating where to continue the listing of datasets.

The beginning of the name of the datasets to be listed.

Specifies the maximum number of datasets to list.

An opaque pagination token indicating where to continue the listing of datasets.

Provides information about the specified dataset, including creation time, dataset ARN, and status.

The response's http status code.

The Amazon Resource Name (ARN) of the resource to which the tag is currently associated.

Specifies the key of the tag to be removed from a specified resource.

The response's http status code.

The name of the inference scheduler being described.

Indicates the status of the inference scheduler.

Specifies how often data is uploaded to the source S3 bucket for the input data. This value is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if you select an offset delay time of five minutes, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don't need to stop and restart the scheduler when uploading new data.

The Amazon Resource Name (ARN) of the ML model of the inference scheduler being described.

Specifies the time at which the inference scheduler was created.

The name of the ML model of the inference scheduler being described.

The Amazon Resource Name (ARN) of the inference scheduler being described.

Specifies information for the output results for the inference scheduler, including the output S3 location.

Specifies the time at which the inference scheduler was last updated, if it was.

The name of the inference scheduler being described.

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

Provides the identifier of the KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment.

The Amazon Resource Name (ARN) of a role with permission to access the data source for the inference scheduler being described.

The response's http status code.

Specifies information for the input data for the data inference job, including data S3 location parameters.

Indicates the status of the data ingestion job.

The Amazon Resource Name (ARN) of the dataset used in the data ingestion job.

Indicates the job ID of the data ingestion job.

The name of the dataset used for the data ingestion job.

The sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.

When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H

Indicates the status of the dataset.

The Amazon Resource Name (ARN) of the specified dataset.

The time at which the dataset was created in Amazon Lookout for Equipment.

The name of the dataset.

Indicates the status of the inference execution.

Specifies the reason for failure when an inference execution has failed.

The Amazon Resource Name (ARN) of the ML model used for the inference execution.

Indicates the time reference in the dataset at which the inference execution began.

The name of the ML model being used for the inference execution.

The Amazon Resource Name (ARN) of the inference scheduler being used for the inference execution.

Indicates the start time at which the inference scheduler began the specific inference execution.

Specifies configuration information for the output results from for the inference execution, including the output S3 location.

Indicates the time reference in the dataset at which the inference execution stopped.

The name of the inference scheduler being used for the inference execution.

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

Indicates the difference between your time zone and Greenwich Mean Time (GMT).

Specifies configuration information for the input data for the inference, including S3 location of input data..

Specifies configuration information for the input data for the inference, including timestamp format and delimiter.

The format of the timestamp, whether Epoch time, or standard, with or without hyphens (-).

Indicates the delimiter character used between items in the data.

The ID number for the AWS KMS key used to encrypt the inference output.

Specifies configuration information for the output results from for the inference, output S3 location.

The prefix for the S3 bucket used for the input data for the inference.

The bucket containing the input dataset for the inference.

The prefix for the S3 bucket used for the output results from the inference.

The bucket containing the output results from the inference

Indicates the status of the inference scheduler.

How often data is uploaded to the source S3 bucket for the input data. This value is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if an offset delay time of five minutes was selected, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don't need to stop and restart the scheduler when uploading new data.

The Amazon Resource Name (ARN) of the ML model used by the inference scheduler.

The name of the ML model used for the inference scheduler.

The Amazon Resource Name (ARN) of the inference scheduler.

The name of the inference scheduler.

The location information for the S3 bucket used for input data for the data ingestion.

The prefix for the S3 location being used for the input data for the data ingestion.

The name of the S3 bucket used for the input data for the data ingestion.

Contains location information for the S3 location being used for label data.

The prefix for the S3 bucket used for the label data.

The name of the S3 bucket holding the label data.

Indicates the status of the ML model.

The Amazon Resource Name (ARN) of the dataset used to create the model.

The Amazon Resource Name (ARN) of the ML model.

The time at which the specific model was created.

The name of the ML model.

The name of the dataset being used for the ML model.

The name of the specific S3 bucket.

The AWS Key Management Service (AWS KMS) key being used to encrypt the S3 object. Without this key, data in the bucket is not accessible.

The key for the specified tag.

The value for the specified tag.