Python Tutorials¶

Getting started¶

A 60-minute Gluon crash coursegetting-started/crash-course/index.html

A quick overview of the core concepts of MXNet using the Gluon API.

Moving from other frameworksgetting-started/to-mxnet/index.html

Guides that ease your transition to MXNet from other framework.

Gluonpackages/gluon/index.html

MXNet’s imperative interface for Python. If you’re new to MXNet, start here!

NP and NPXpackages/np/index.html

This section contains the mxnet.np and mxnet.npx usage hints.

Autograd API/api/python/docs/tutorials/packages/autograd/index.html

How to use Automatic Differentiation with the Autograd API.

Improving Performanceperformance/index.html

How to get the best performance from MXNet.

Profilerperformance/backend/profiler.html

How to profile MXNet models.

Compression: int8performance/compression/int8.html

How to use int8 in your model to boost training speed.

oneDNNperformance/backend/dnnl/index.html

How to get the most from your CPU by using oneDNN.

TVMperformance/backend/tvm.html

How to use TVM to boost performance.

MXNet on EC2deploy/run-on-aws/use_ec2.html

How to deploy MXNet on an Amazon EC2 instance.

MXNet on SageMakerdeploy/run-on-aws/use_sagemaker.html

How to run MXNet using Amazon SageMaker.

Coming Soon (CustomOps and Custom Operators)

To learn more about using MXNet to implement various deep learning algorithms from scratch, we recommend the Dive into Deep Learning book.
Check out the API Reference docs.

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