Use Scikit-learn with Amazon SageMaker - Amazon SageMaker

Use Scikit-learn with Amazon SageMaker

You can use Amazon SageMaker to train and deploy a model using custom Scikit-learn code. The SageMaker Python SDK Scikit-learn estimators and models and the SageMaker open-source Scikit-learn container make writing a Scikit-learn script and running it in SageMaker easier.

What do you want to do?

I want to use Scikit-learn for data processing, feature engineering, or model evaluation in SageMaker.

For a sample Jupyter notebook, see https://github.com/awslabs/amazon-sagemaker-examples/tree/master/sagemaker_processing/scikit_learn_data_processing_and_model_evaluation.

For documentation, see ReadTheDocs.

I want to train a custom Scikit-learn model in SageMaker.

For a sample Jupyter notebook, see https://github.com/awslabs/amazon-sagemaker-examples/tree/master/sagemaker-python-sdk/scikit_learn_iris.

For documentation, see Train a Model with Scikit-learn.

I have a Scikit-learn model that I trained in SageMaker, and I want to deploy it to a hosted endpoint.

For more information, see Deploy Scikit-learn models.

I have a Scikit-learn model that I trained outside of SageMaker, and I want to deploy it to a SageMaker endpoint

For more information, see Deploy Endpoints from Model Data.

I want to see the API documentation for Amazon SageMaker Python SDK Scikit-learn classes.

For more information, see Scikit-learn Classes.

I want to see information about SageMaker Scikit-learn containers.

For more information, see SageMaker Scikit-learn Container GitHub repository.

For general information about writing Scikit-learn training scripts and using Scikit-learn estimators and models with SageMaker, see Using Scikit-learn with the SageMaker Python SDK.

Scikit-learn versions supported by the Amazon SageMaker Scikit-learn container: 0.20.0, 0.23-1.