Resources for using Apache MXNet with Amazon SageMaker

The Amazon SageMaker Python SDK MXNet estimators and models and the SageMaker open-source MXNet container make writing a MXNet script and running it in SageMaker easier. The following section provides reference material you can use to learn how to use SageMaker to train and deploy a model using custom MXNet code.

What do you want to do?

I want to train a custom MXNet model in SageMaker.

For documentation, see Train a Model with MXNet.

I have an MXNet model that I trained in SageMaker, and I want to deploy it to a hosted endpoint.

For more information, see Deploy MXNet models.

I have an MXNet 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 MXNet classes.

For more information, see MXNet Classes.

I want to find the SageMaker MXNet container repository.

For more information, see SageMaker MXNet Container GitHub repository.

I want to find information about MXNet versions supported by AWS Deep Learning Containers.

For more information, see Available Deep Learning Container Images.

For general information about writing MXNet script mode training scripts and using MXNet script mode estimators and models with SageMaker, see Using MXNet with the SageMaker Python SDK.