Amazon SageMaker
Developer Guide

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Use Scikit-learn with Amazon SageMaker

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

What do you want to do?

I want to train a custom Scikit-learn model in Amazon 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 Amazon SageMaker, and I want to deploy it to a hosted endpoint.

Deploy Scikit-learn models.

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

Deploy Endpoints from Model Data.

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

Scikit-learn Classes

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

https://github.com/aws/sagemaker-scikit-learn-container.

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

For information about Scikit-learn versions supported by the Amazon SageMaker Scikit-learn container, see https://github.com/aws/sagemaker-python-sdk/blob/master/src/sagemaker/sklearn/README.rst.

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