# Using Scikit-Learn Pipelines with Amazon SageMaker

In this notebook, we will have a look at which features from Amazon SageMaker can help you bring your ML workloads based on Scikit-Learn, and in particular Scikit-Learn Pipelines, to the AWS cloud in order to create scheduled pipelines of preprocessing and training, as well as having endpoints for generating predictions in real-time.
We will do this in three different modes, involving different features and complexity levels:

- Level 1: SKLearn Pipeline in the Training script
- Level 2 : Preprocessing with Processing, Training, Transformation & Inference in one Script
- Level 3 : SageMaker Inference Pipelines

## 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.