AWS Machine Learning Blog

Tag: Deep Learning AMI

AWS Deep Learning AMI Now Supports PyTorch, Keras 2 and Latest Deep Learning Frameworks

Today, we’re pleased to announce an update to the AWS Deep Learning AMI. The AWS Deep Learning AMI, which lets you spin up a complete deep learning environment on AWS in a single click, now includes PyTorch, Keras 1.2 and 2.0 support, along with popular machine learning frameworks such as TensorFlow, Caffe2 and Apache MXNet. […]

Build an Autonomous Vehicle on AWS and Race It at the re:Invent Robocar Rally

Autonomous vehicles are poised to take to our roads in massive numbers in the coming years. This has been made possible due to advances in deep learning and its application to autonomous driving. In this post, we take you through a tutorial that shows you how to build a remote control (RC) vehicle that uses […]

Get Started with Deep Learning Using the AWS Deep Learning AMI

Whether you’re new to deep learning or want to build advanced deep learning projects in the cloud, it’s easy to get started by using AWS. For users of all levels, AWS recommends Amazon SageMaker, a fully managed machine learning (ML) platform. The platform makes it straightforward to quickly and easily build, train, and deploy ML […]

The AWS Deep Learning AMI for Ubuntu is Now Available with CUDA 8, Ubuntu 16, and the Latest Versions of Deep Learning Frameworks

The AWS Deep Learning AMI lets you build and scale deep learning applications in the cloud, at any scale. The AMI comes pre-installed with popular deep learning frameworks, to let you to train sophisticated, custom AI models, experiment with new algorithms, or to learn new skills and techniques. The latest release of the AWS Deep […]

AWS and NVIDIA Expand Deep Learning Partnership at GTC 2017

This year at NVIDIA’s GPU Technology Conference, AWS and NVIDIA partnered on multiple initiatives. The first is an exciting new Volta-based GPU instance that we think will completely change the face of the AI developer world through a 3x speedup on LSTM training. Second, we are announcing plans to train 100,000+ developers through the Deep […]