Apache MXNet is a fast and scalable training and inference framework with an easy-to-use, concise API for machine learning.
MXNet includes the Gluon interface that allows developers of all skill levels to get started with deep learning on the cloud, on edge devices, and on mobile apps. In just a few lines of Gluon code, you can build linear regression, convolutional networks and recurrent LSTMs for object detection, speech recognition, recommendation, and personalization.
Get started using MXNet and Gluon on AWS by launching an AWS Deep Learning AMI, available in several versions for both Amazon Linux and Ubuntu.
Grab sample code, notebooks, and tutorial content at the GitHub project page.
Benefits of deep learning using MXNet
Ease-of-Use with Gluon
For IoT & the Edge
Flexibility & Choice
MXNet case studies
Blog posts & articles
Explore deep learning on AWS
With the AWS Deep Learning AMIs, you can train custom models, experiment with new algorithms, and learn new deep learning skills and techniques. The AMIs come in several flavors including pre-installed, open source deep learning frameworks such as Apache MXNet and Gluon, TensorFlow, Microsoft Cognitive Toolkit, Caffe, Caffe2, Theano, Torch, PyTorch, and Keras. There is no additional charge to use the AMIs—you pay only for the AWS resources needed to store and run your applications. More >