@aws-sdk/client-machine-learning

Description

AWS SDK for JavaScript MachineLearning Client for Node.js, Browser and React Native.

Definition of the public APIs
exposed by Amazon Machine Learning

Installing

To install this package, simply type add or install @aws-sdk/client-machine-learning
using your favorite package manager:
- npm install @aws-sdk/client-machine-learning
- yarn add @aws-sdk/client-machine-learning
- pnpm add @aws-sdk/client-machine-learning

Getting Started

$3

The AWS SDK is modulized by clients and commands.
To send a request, you only need to import the MachineLearningClient and
the commands you need, for example DescribeMLModelsCommand:

``js
// ES5 example
const { MachineLearningClient, DescribeMLModelsCommand } = require("@aws-sdk/client-machine-learning");
`

`ts
// ES6+ example
import { MachineLearningClient, DescribeMLModelsCommand } from "@aws-sdk/client-machine-learning";
`

$3

To send a request, you:

- Initiate client with configuration (e.g. credentials, region).
- Initiate command with input parameters.
- Call send operation on client with command object as input.
- If you are using a custom http handler, you may call destroy() to close open connections.

`js
// a client can be shared by different commands.
const client = new MachineLearningClient({ region: "REGION" });

const params = { /* input parameters / };
const command = new DescribeMLModelsCommand(params);
`

#### Async/await

We recommend using await
operator to wait for the promise returned by send operation as follows:

`js
// async/await.
try {
const data = await client.send(command);
// process data.
} catch (error) {
// error handling.
} finally {
// finally.
}
`

Async-await is clean, concise, intuitive, easy to debug and has better error handling
as compared to using Promise chains or callbacks.

#### Promises

You can also use Promise chaining
to execute send operation.

`js
client.send(command).then(
(data) => {
// process data.
},
(error) => {
// error handling.
}
);
`

Promises can also be called using .catch() and .finally() as follows:

`js
client
.send(command)
.then((data) => {
// process data.
})
.catch((error) => {
// error handling.
})
.finally(() => {
// finally.
});
`

#### Callbacks

We do not recommend using callbacks because of callback hell,
but they are supported by the send operation.

`js
// callbacks.
client.send(command, (err, data) => {
// process err and data.
});
`

#### v2 compatible style

The client can also send requests using v2 compatible style.
However, it results in a bigger bundle size and may be dropped in next major version. More details in the blog post
on modular packages in AWS SDK for JavaScript

`ts
import * as AWS from "@aws-sdk/client-machine-learning";
const client = new AWS.MachineLearning({ region: "REGION" });

// async/await.
try {
const data = await client.describeMLModels(params);
// process data.
} catch (error) {
// error handling.
}

// Promises.
client
.describeMLModels(params)
.then((data) => {
// process data.
})
.catch((error) => {
// error handling.
});

// callbacks.
client.describeMLModels(params, (err, data) => {
// process err and data.
});
`

$3

When the service returns an exception, the error will include the exception information,
as well as response metadata (e.g. request id).

`js
try {
const data = await client.send(command);
// process data.
} catch (error) {
const { requestId, cfId, extendedRequestId } = error.$metadata;
console.log({ requestId, cfId, extendedRequestId });
/**
* The keys within exceptions are also parsed.
* You can access them by specifying exception names:
* if (error.name === 'SomeServiceException') {
* const value = error.specialKeyInException;
* }
*/
}
`

Getting Help

Please use these community resources for getting help.
We use the GitHub issues for tracking bugs and feature requests, but have limited bandwidth to address them.

- Visit Developer Guide
or API Reference.
- Check out the blog posts tagged with aws-sdk-js
on AWS Developer Blog.
- Ask a question on StackOverflow and tag it with aws-sdk-js.
- Join the AWS JavaScript community on gitter.
- If it turns out that you may have found a bug, please open an issue.

To test your universal JavaScript code in Node.js, browser and react-native environments,
visit our code samples repo.

Contributing

This client code is generated automatically. Any modifications will be overwritten the next time the @aws-sdk/client-machine-learning` package is updated.
To contribute to client you can check our generate clients scripts.

License

This SDK is distributed under the
Apache License, Version 2.0,
see LICENSE for more information.

Client Commands (Operations List)

AddTags

Command API Reference / Input / Output

CreateBatchPrediction

Command API Reference / Input / Output

CreateDataSourceFromRDS

Command API Reference / Input / Output

CreateDataSourceFromRedshift

Command API Reference / Input / Output

CreateDataSourceFromS3

Command API Reference / Input / Output

CreateEvaluation

Command API Reference / Input / Output

CreateMLModel

Command API Reference / Input / Output

CreateRealtimeEndpoint

Command API Reference / Input / Output

DeleteBatchPrediction

Command API Reference / Input / Output

DeleteDataSource

Command API Reference / Input / Output

DeleteEvaluation

Command API Reference / Input / Output

DeleteMLModel

Command API Reference / Input / Output

DeleteRealtimeEndpoint

Command API Reference / Input / Output

DeleteTags

Command API Reference / Input / Output

DescribeBatchPredictions

Command API Reference / Input / Output

DescribeDataSources

Command API Reference / Input / Output

DescribeEvaluations

Command API Reference / Input / Output

DescribeMLModels

Command API Reference / Input / Output

DescribeTags

Command API Reference / Input / Output

GetBatchPrediction

Command API Reference / Input / Output

GetDataSource

Command API Reference / Input / Output

GetEvaluation

Command API Reference / Input / Output

GetMLModel

Command API Reference / Input / Output

Predict

Command API Reference / Input / Output

UpdateBatchPrediction

Command API Reference / Input / Output

UpdateDataSource

Command API Reference / Input / Output

UpdateEvaluation

Command API Reference / Input / Output

UpdateMLModel

Command API Reference / Input / Output