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AmazonML

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By serg.osipchuk
Updated 2 months ago
Machine Learning
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AmazonML API Overview

Connect to the Amazon Machine Learning API to build machine learning models to find patterns in data. Test the machine learning API call and export the code. Use cases include big data analysis such as fraud detection, forecasting demand, targeted marketing and click prediction.

Amazon's Machine Learning API charges by the hour and by number of predictions. Read more here: https://aws.amazon.com/machine-learning/pricing/

AmazonML

AmazonML Package

Amazon Machine Learning is a managed service for building ML models and generating predictions, enabling the development of robust, scalable smart applications.

  • Domain: amazon.com
  • Credentials: apiKey, apiSecret

How to get credentials:

  1. Go to Amazon Console
  2. Log in or create new account
  3. In the dropdown from your username, select 'My Security Credentials'
  4. On the left side, select 'Groups' and create a new Group with the necessary polices
  5. Create new user and assign to existing group
  6. After creating user you will see credentials

Custom datatypes:

Datatype Description Example
Datepicker String which includes date and time 2016-05-28 00:00:00
Map String which includes latitude and longitude coma separated 50.37, 26.56
List Simple array ["123", "sample"]
Select String with predefined values sample
Array Array of objects [{"Second name":"123","Age":"12","Photo":"sdf","Draft":"sdfsdf"},{"name":"adi","Second name":"bla","Age":"4","Photo":"asfserwe","Draft":"sdfsdf"}]

AmazonML.addTags

Adds one or more tags to an object, up to a limit of 10. Each tag consists of a key and an optional value. If you add a tag using a key that is already associated with the ML object, AddTags updates the tag's value.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
resourceId String The ID of the ML object to tag. For example, exampleModelId.
resourceType Select The type of the ML object to tag. Valid Values: BatchPrediction; DataSource; Evaluation; MLModel
tags Array Array of objects. The key-value pairs to use to create tags. If you specify a key without specifying a value, Amazon ML creates a tag with the specified key and a value of null. See README for more details.

tags format

[
    {
        "Key": "Tag1", 
        "Value": "new"
    }
]

AmazonML.createBatchPrediction

Generates predictions for a group of observations.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
dataSourceId String The ID of the DataSource that points to the group of observations to predict.
predictionId String A user-supplied ID that uniquely identifies the BatchPrediction.
modelId String The ID of the MLModel that will generate predictions for the group of observations.
outputUri String The location of an Amazon Simple Storage Service (Amazon S3) bucket or directory to store the batch prediction results.
predictionName String A user-supplied name or description of the BatchPrediction. BatchPredictionName can only use the UTF-8 character set.

AmazonML.createDataSourceFromRDS

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
dataSourceId String A user-supplied ID that uniquely identifies the DataSource. Typically, an Amazon Resource Number (ARN) becomes the ID for a DataSource.
computeStatistics String The compute statistics for a DataSource. The statistics are generated from the observation data referenced by a DataSource. Treu or false.
roleARN String The role that Amazon ML assumes on behalf of the user to create and activate a data pipeline in the user's account and copy data using the SelectSqlQuery query from Amazon RDS to Amazon S3.
passwordRDS String The password of RDS.
usernameRDS String The username of RDS.
dbName String The name of the Amazon RDS database.
instanceId String A unique identifier for the Amazon RDS database instance.
resourceRole String A role (DataPipelineDefaultResourceRole) assumed by an EC2 instance to carry out the copy task from Amazon RDS to Amazon Simple Storage Service (Amazon S3).
S3StagingLocation String The Amazon S3 location for staging Amazon RDS data. The data retrieved from Amazon RDS using SelectSqlQuery is stored in this location.
securityGroupIds List Array of strings. The security information to use to access an RDS DB instance. You need to set up appropriate ingress rules for the security entity IDs provided to allow access to the Amazon RDS instance.
sqlQuery String A query that is used to retrieve the observation data for the Datasource.
serviceRole String A role (DataPipelineDefaultRole) assumed by the AWS Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3.
subnetId String The subnet ID to be used to access a VPC-based RDS DB instance. This attribute is used by Data Pipeline to carry out the copy task from Amazon RDS to Amazon S3.
dataSourceName String A user-supplied name or description of the DataSource.
dataRearrangement JSON A JSON string that represents the splitting and rearrangement requirements for the Datasource. Sample - "{"splitting":{"percentBegin":10,"percentEnd":60}}"
dataSchema JSON A JSON string representing the schema. This is not required if DataSchemaUri is specified.
dataSchemaUri String The Amazon S3 location of the DataSchema.

securityGroupIds format

["sg-XXXXXX", "sg-XXXXXX"]

AmazonML.createDataSourceFromRedshift

(BETA) Creates a DataSource from a database hosted on an Amazon Redshift cluster.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
dataSourceId String A user-supplied ID that uniquely identifies the DataSource. Typically, an Amazon Resource Number (ARN) becomes the ID for a DataSource.
computeStatistics String The compute statistics for a DataSource. The statistics are generated from the observation data referenced by a DataSource. Treu or false.
roleARN String The role that Amazon ML assumes on behalf of the user to create and activate a data pipeline in the user's account and copy data using the SelectSqlQuery query from Amazon RDS to Amazon S3.
password String The password of Redshift cluster.
username String The username of Redshift cluster.
dbName String The name of the Amazon Redshift database.
clusterId String The unique ID for the Amazon Redshift cluster.
S3StagingLocation String The Amazon S3 location for staging Amazon RDS data. The data retrieved from Amazon RDS using SelectSqlQuery is stored in this location.
sqlQuery String A query that is used to retrieve the observation data for the Datasource.
dataSourceName String A user-supplied name or description of the DataSource.
dataRearrangement JSON A JSON string that represents the splitting and rearrangement requirements for the Datasource. Sample - "{"splitting":{"percentBegin":10,"percentEnd":60}}"
dataSchema JSON A JSON string representing the schema. This is not required if DataSchemaUri is specified.
dataSchemaUri String The Amazon S3 location of the DataSchema.

AmazonML.createDataSourceFromS3

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
dataSourceId String A user-supplied ID that uniquely identifies the DataSource. Typically, an Amazon Resource Number (ARN) becomes the ID for a DataSource.
dataLocation String The Amazon S3 location of the observation data.
computeStatistics String The compute statistics for a DataSource. The statistics are generated from the observation data referenced by a DataSource. Treu or false.
dataSourceName String A user-supplied name or description of the DataSource.
dataRearrangement JSON A JSON string that represents the splitting and rearrangement requirements for the Datasource. Sample - "{"splitting":{"percentBegin":10,"percentEnd":60}}"
dataSchema JSON A JSON string representing the schema. This is not required if DataSchemaUri is specified.
dataSchemaLocation String The Amazon S3 location of the DataSchema.

AmazonML.createEvaluation

Creates a new Evaluation of an MLModel. An MLModel is evaluated on a set of observations associated to a DataSource.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
dataSourceId String The ID of the DataSource for the evaluation. The schema of the DataSource must match the schema used to create the MLModel.
evaluationId String A user-supplied ID that uniquely identifies the Evaluation.
modelId String The ID of the MLModel to evaluate.
evaluationName String A user-supplied name or description of the Evaluation.

AmazonML.createMLModel

Creates a new Evaluation of an MLModel. An MLModel is evaluated on a set of observations associated to a DataSource.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
modelId String A user-supplied ID that uniquely identifies the MLModel.
modelType Select The category of supervised learning that this MLModel will address. Choose from the following types: Choose REGRESSION if the MLModel will be used to predict a numeric value. Choose BINARY if the MLModel result has two possible values. Choose MULTICLASS if the MLModel result has a limited number of values.
trainingDataSourceId String The ID of DataSource that points to the training data.
modelName String A user-supplied name or description of the MLModel.
parameters JSON A list of the training parameters in the MLModel. The list is implemented as a map of key-value pairs. See README for more details.
recipe String The data recipe for creating the MLModel. You must specify either the recipe or its URI. If you don't specify a recipe or its URI, Amazon ML creates a default.
recipeUri String The Amazon Simple Storage Service (Amazon S3) location and file name that contains the MLModel recipe. You must specify either the recipe or its URI. If you don't specify a recipe or its URI, Amazon ML creates a default.

parameters format

[
    {
    "Key": "sgd.maxMLModelSizeInBytes",
        "Value": "33554432"
    },
    {
    "Key": "sgd.shuffleType",
        "Value": "none"
    }
]

AmazonML.createRealtimeEndpoint

Creates a real-time endpoint for the MLModel.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
modelId String The ID assigned to the MLModel during creation.

AmazonML.describePredictions

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
equal String The equal to operator.
filterVariable String Use one of the following variables to filter a list: CreatedAt - Sets the search criteria to the BatchPrediction creation date. Status - Sets the search criteria to the BatchPrediction status. Name - Sets the search criteria to the contents of the BatchPrediction Name. IAMUser - Sets the search criteria to the user account that invoked the BatchPrediction creation. MLModelId - Sets the search criteria to the MLModel used in the BatchPrediction. DataSourceId - Sets the search criteria to the DataSource used in the BatchPrediction. DataURI - Sets the search criteria to the data file(s) used in the BatchPrediction. The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory.
greaterOrEqual String The greater than or equal to operator.
greaterThan String The greater than operator.
lessOrEqual String The less than or equal to operator.
limit String The number of pages of information to include in the result. The range of acceptable values is 1 through 100. The default value is 100.
lessThen String The less than operator.
notEqual String The not equal to operator.
nextToken String An ID of the page in the paginated results.
prefix String A string that is found at the beginning of a variable, such as Name or Id.
sortOrder Select A two-value parameter that determines the sequence of the resulting list of MLModels. Valid Values: asc; dsc

AmazonML.describeDataSources

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
equal String The equal to operator.
filterVariable String Use one of the following variables to filter a list. Valid Values: CreatedAt; LastUpdatedAt; Status; Name; DataLocationS3; IAMUser
greaterOrEqual String The greater than or equal to operator.
greaterThan String The greater than operator.
lessOrEqual String The less than or equal to operator.
limit String The number of pages of information to include in the result. The range of acceptable values is 1 through 100. The default value is 100.
lessThen String The less than operator.
notEqual String The not equal to operator.
nextToken String An ID of the page in the paginated results.
prefix String A string that is found at the beginning of a variable, such as Name or Id.
sortOrder Select A two-value parameter that determines the sequence of the resulting list of MLModels. Valid Values: asc; dsc

AmazonML.describeEvaluations

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
equal String The equal to operator.
filterVariable String Use one of the following variables to filter a list. Valid Values: CreatedAt; LastUpdatedAt; Status; Name; IAMUser; MLModelId; DataSourceId; DataURI
greaterOrEqual String The greater than or equal to operator.
greaterThan String The greater than operator.
lessOrEqual String The less than or equal to operator.
limit String The number of pages of information to include in the result. The range of acceptable values is 1 through 100. The default value is 100.
lessThen String The less than operator.
notEqual String The not equal to operator.
nextToken String An ID of the page in the paginated results.
prefix String A string that is found at the beginning of a variable, such as Name or Id.
sortOrder Select A two-value parameter that determines the sequence of the resulting list of MLModels. Valid Values: asc; dsc

AmazonML.describeModels

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
equal String The equal to operator.
filterVariable String Use one of the following variables to filter a list. Valid Values: CreatedAt; LastUpdatedAt; Status; Name; IAMUser; TrainingDataSourceId; RealtimeEndpointStatus; MLModelType; Algorithm; TrainingDataURI
greaterOrEqual String The greater than or equal to operator.
greaterThan String The greater than operator.
lessOrEqual String The less than or equal to operator.
limit String The number of pages of information to include in the result. The range of acceptable values is 1 through 100. The default value is 100.
lessThen String The less than operator.
notEqual String The not equal to operator.
nextToken String An ID of the page in the paginated results.
prefix String A string that is found at the beginning of a variable, such as Name or Id.
sortOrder Select A two-value parameter that determines the sequence of the resulting list of MLModels. Valid Values: asc; dsc

AmazonML.describeTags

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
resourceId String The ID of the ML object. For example, exampleModelId.
resourceType Select The type of the ML object. Valid Values: BatchPrediction; DataSource; Evaluation; MLModel

AmazonML.getPrediction

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
predictionId String An ID assigned to the BatchPrediction at creation.

AmazonML.getDataSource

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
dataSourceId String The ID assigned to the DataSource at creation.
verbose Boolean Specifies whether the GetDataSource operation should return DataSourceSchema. True or false.

AmazonML.getEvaluation

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
evaluationId String The ID of the Evaluation to retrieve.

AmazonML.getModel

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

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
modelId String The ID assigned to the MLModel at creation.
verbose Boolean Specifies whether the GetMLModel operation should return Recipe. True or false.

AmazonML.predict

Generates a prediction for the observation using the specified ML Model.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
modelId String The ID assigned to the MLModel at creation.
endpoint String Endpoint for predict. Pattern: https://[a-zA-Z0-9-.]*.amazon(aws)?.com[/]?
record Array A map of variable name-value pairs that represent an observation. See README for more details.

record format

{
    "ExampleData" : "exampleValue"
}

AmazonML.updatePrediction

Updates the BatchPredictionName of a BatchPrediction.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
predictionId String The ID assigned to the BatchPrediction during creation.
predictionName String A new user-supplied name or description of the BatchPrediction.

AmazonML.updateDataSource

Updates the DataSourceName of a DataSource.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
dataSourceId String The ID assigned to the DataSource during creation.
dataSourceName String A new user-supplied name or description of the DataSource that will replace the current description.

AmazonML.updateEvaluation

Updates the EvaluationName of an Evaluation.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
evaluationId String The ID assigned to the Evaluation during creation.
evaluationName String A new user-supplied name or description of the Evaluation that will replace the current content.

AmazonML.updateModel

Updates the MLModelName and the ScoreThreshold of an MLModel.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
modelId String The ID assigned to the MLModel during creation.
modelName String A user-supplied name or description of the MLModel.
scoreThreshold String The ScoreThreshold used in binary classification MLModel that marks the boundary between a positive prediction and a negative prediction.

AmazonML.deleteTags

Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover deleted tags. If you specify a tag that doesn't exist, Amazon ML ignores it.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
resourceId String The ID of the tagged ML object. For example, exampleModelId.
resourceType Select The type of the tagged ML object. Valid Values: BatchPrediction; DataSource; Evaluation; MLModel
tagKeys List List of tags. One or more tags to delete. Example: ["tag1","tag2",…]

tagKeys format

["Tag1"]

AmazonML.deleteRealtimeEndpoint

Deletes a real time endpoint of an MLModel.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
modelId String The ID assigned to the MLModel during creation.

AmazonML.deleteEvaluation

Assigns the DELETED status to an Evaluation, rendering it unusable.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
evaluationId String A user-supplied ID that uniquely identifies the Evaluation to delete.

AmazonML.deletePrediction

Assigns the DELETED status to a BatchPrediction, rendering it unusable.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
predictionId String A user-supplied ID that uniquely identifies the BatchPrediction.

AmazonML.deleteDataSource

Assigns the DELETED status to a DataSource, rendering it unusable.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
dataSourceId String A user-supplied ID that uniquely identifies the DataSource.

AmazonML.deleteModel

Assigns the DELETED status to an MLModel, rendering it unusable.

Field Type Description
apiKey credentials API key obtained from Amazon.
apiSecret credentials API secret obtained from Amazon.
region String Region.
modelId String A user-supplied ID that uniquely identifies the MLModel.
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Install SDK for NodeJS

Installing

To utilize unirest for node.js install the the npm module:

$ npm install unirest

After installing the npm package you can now start simplifying requests like so:

var unirest = require('unirest');

Creating Request

unirest.post("https://AmazonMLserg-osipchukV1.p.rapidapi.com/addTags")
.header("X-RapidAPI-Host", "undefined")
.header("X-RapidAPI-Key", "undefined")
.header("Content-Type", "application/x-www-form-urlencoded")
.end(function (result) {
  console.log(result.status, result.headers, result.body);
});
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