<commit_before># MXNet FAQ

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](../tutorials/index.md).


## Modeling
* [How do I fine-tune pre-trained models to a new dataset?](http://mxnet.io/faq/finetune.html)

* [How do I work with variable-length input in MXNet (bucketing)?](http://mxnet.io/faq/bucketing.html)

* [How do I visualize neural networks as computation graphs?](http://mxnet.io/faq/visualize_graph.html)


## Scale
* [How can I train with multiple CPU/GPUs on a single machine with data parallelism?](http://mxnet.io/faq/multi_devices.html)

* [How can I train using multiple machines with data parallelism?](http://mxnet.io/faq/distributed_training.html)

* [How can I train using multiple GPUs with model parallelism?](http://mxnet.io/faq/model_parallel_lstm.html)


## Speed
* [How do I use gradient compression with distributed training?](http://mxnet.io/faq/gradient_compression.html)

* [Can I use nnpack to improve the CPU performance of MXNet?](http://mxnet.io/faq/nnpack.html)

* [What are the best setup and data-handling tips and tricks for improving speed?](http://mxnet.io/faq/perf.html)


## Deployment Environments
* [Can I run MXNet on smart or mobile devices?](http://mxnet.io/faq/smart_device.html)

* [How to use data from S3 for training?](s3_integration.md)

* [How to setup MXNet on AWS?](http://docs.aws.amazon.com/mxnet/latest/dg/mxnet-on-ec2-instance.html)<commit_msg>Added Module vs Gluon API FAQ (#11038)<commit_after># MXNet FAQ

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](../tutorials/index.md).

## API

* [What's the difference between the Module and Gluon APIs for Python?](http://mxnet.io/api/python/index.html)

## Modeling
* [How do I fine-tune pre-trained models to a new dataset?](http://mxnet.io/faq/finetune.html)

* [How do I work with variable-length input in MXNet (bucketing)?](http://mxnet.io/faq/bucketing.html)

* [How do I visualize neural networks as computation graphs?](http://mxnet.io/faq/visualize_graph.html)


## Scale
* [How can I train with multiple CPU/GPUs on a single machine with data parallelism?](http://mxnet.io/faq/multi_devices.html)

* [How can I train using multiple machines with data parallelism?](http://mxnet.io/faq/distributed_training.html)

* [How can I train using multiple GPUs with model parallelism?](http://mxnet.io/faq/model_parallel_lstm.html)


## Speed
* [How do I use gradient compression with distributed training?](http://mxnet.io/faq/gradient_compression.html)

* [Can I use nnpack to improve the CPU performance of MXNet?](http://mxnet.io/faq/nnpack.html)

* [What are the best setup and data-handling tips and tricks for improving speed?](http://mxnet.io/faq/perf.html)


## Deployment Environments
* [Can I run MXNet on smart or mobile devices?](http://mxnet.io/faq/smart_device.html)

* [How to use data from S3 for training?](s3_integration.md)

* [How to setup MXNet on AWS?](http://docs.aws.amazon.com/mxnet/latest/dg/mxnet-on-ec2-instance.html)
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