MXNet How To¶
This section addresses common questions about how to use MXNet. These include performance issues, e.g., how to train with multiple GPUs. They also include workflow questions, e.g., how to visualize a neural network computation graph. These answers are fairly focused. For more didactic, self-contained introductions to neural networks and full working examples, visit the tutorials section.
- Can I run MXNet on smart or mobile devices?
- How to use data from S3 for training?
- How to setup MXNet on AWS?
- How to do distributed training using MXNet on AWS?
- How do I run MXNet on a Raspberry Pi for computer vision?
- How do I run Keras 1.2.2 with mxnet backend?
- How to convert MXNet models to Apple CoreML format?
Extend and Contribute to MXNet¶
Questions about Using MXNet¶
If you are not sure of how to use MXNet for something, or have questions about applying it to a particular kind of problem, please post a question at Stackoverflow with tag -
mxnet. You can view StackOverflow questions about mxnet here.
We track bugs and new feature requests in the MXNet Github repo in the issues folder: mxnet/issues.