Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
SPDX-License-Identifier: CC-BY-SA-4.0

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

What do you want to do?

I want to train a custom MXNet model in Amazon SageMaker.
For a sample Jupyter notebook, see https://github.com/awslabs/amazon-sagemaker-examples/tree/master/sagemaker-python-sdk/mxnet_mnist.
For documentation, see Train a Model with MXNet.

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

I have an MXNet 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 MXNet classes.
MXNet Classes

I want to see information about Amazon SageMaker MXNet containers.
https://github.com/aws/sagemaker-mxnet-container.

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

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