## Develop your ML project with Amazon SageMaker

![SageMaker Workshop](/static/sagemaker.jpeg)

In this workshop, learn how to develop a full ML project end to end with Amazon SageMaker. Start with data exploration and analysis, data cleansing, and feature engineering with SageMaker Data Wrangler. Then, store features in SageMaker Feature Store, extract features for training with SageMaker Processing, train a model with SageMaker training, and then deploy it with SageMaker hosting. Also, learn how to use SageMaker Studio as an IDE and SageMaker Pipelines for orchestrating the ML end-to-end workflow.

## Security

See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.

## License

This library is licensed under the MIT-0 License. See the LICENSE file.