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