Apache MXNet is Amazon's deep learning framework of choice because of its flexibility, scalability, and performance across a wide variety of use cases, including IoT and mobile. If you're new to deep learning, or just new to deep learning on the cloud, we think it's a great place to start. Use these self-service guides to build and launch your own deep learning project on AWS with NVIDIA GPU computing.
Quick, step-by-step tutorials and datasets to get you started with deep learning.
The AWS Deep Learning AMI provides the fastest way to deploy MXNet, and all other major frameworks, on AWS at no additional cost.
Use a pre-built notebook to get up and running quickly and learn how MXNet works.
The AWS public datasets collection provides a wide variety of freely available data for your use.
Freely available notebooks to help you quickly build new applications and learn more about MXNet.
♦ Use pre-trained models from the model zoo
♦ Quickly predict image content using AWS Lambda and AWS API Gateway
♦ Use matrix factorization to understand user behavior
♦ Predict customer recommendations with accuracy
♦ Train language models with a multilayer recurrent neural network
♦ Generate new speech based on character-level training
Amazon EC2 P2 instances allow you to take advantage of MXNet's horizontal scaling efficiency at low cost. These instances are ideally suited for machine learning and deep learning applications.
