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https://github.com/aws/sagemaker-example-notebooks-testing

A continuous integration (CI) system for 📓 Jupyter notebooks, built using 🧠 Amazon SageMaker.
https://github.com/aws/sagemaker-example-notebooks-testing

aws cdk ci continuous-integration deep-learning jupyter-notebook machine-learning python sagemaker

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A continuous integration (CI) system for 📓 Jupyter notebooks, built using 🧠 Amazon SageMaker.

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:warning: **Warning**: This repository is experimental software designed for trial use. It may change significantly in the future and there is no guarantee of support. Please do use it and give us feedback on what we could improve, but take its experimental nature into account.

![SageMaker](https://github.com/aws/sagemaker-example-notebooks-testing/raw/main/branding/icon/sagemaker-banner.png)

# SageMaker Example Notebooks Testing

A continuous integration (CI) system for Jupyter notebooks, built using Amazon SageMaker.

## :books: Background

[Amazon SageMaker](https://aws.amazon.com/sagemaker/) is a fully managed service for data science and machine learning (ML) workflows.
You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models.

The [SageMaker example notebooks](https://sagemaker-examples.readthedocs.io/en/latest/) are Jupyter notebooks that demonstrate the usage of Amazon SageMaker.

This **SageMaker Example Notebooks Testing** repository contains the code for the open-source CI system for the example notebooks.
It can be repurposed to build a CI system for your own Jupyter notebooks on SageMaker.

## :balance_scale: License

This library is licensed under the [Apache 2.0 License](http://aws.amazon.com/apache2.0/).
For more details, please take a look at the [LICENSE](https://github.com/aws/sagemaker-example-notebooks-testing/blob/main/LICENSE) file.

## :handshake: Contributing

Contributions are welcome!
Please read our [contributing guidelines](https://github.com/aws/sagemaker-example-notebooks-testing/blob/main/CONTRIBUTING.md)
if you'd like to open an issue or submit a pull request.