New AWS Deep Learning Containers with Tensorflow 1.15, PyTorch 1.3.1, and MXNet 1.6.0-rc0
The AWS Deep Learning Containers are available today with the latest framework versions of Tensorflow 1.15, PyTorch 1.3.1, and MXNet 1.6.0-rc0. You can launch the new versions of Deep Learning Container on Amazon Sagemaker, Amazon Elastic Kubernetes Service (Amazon EKS), self-managed Kubernetes on Amazon EC2, and Amazon Elastic Container Service (Amazon ECS). For a complete list of frameworks and versions supported by the AWS Deep Learning Containers, see release notes.
The AWS Deep Learning Containers are available today with the latest framework versions of Tensorflow 1.15, PyTorch 1.3.1, and MXNet 1.6.0-rc0. You can launch the new versions of Deep Learning Container on Amazon Sagemaker, Amazon Elastic Kubernetes Service (Amazon EKS), self-managed Kubernetes on Amazon EC2, and Amazon Elastic Container Service (Amazon ECS). For a complete list of frameworks and versions supported by the AWS Deep Learning Containers, see release notes.
More details can be found in marketplace, and a list of available containers can be found in our documentation. Get started quickly with the AWS Deep Learning Containers using the getting-started guides and beginner to advanced level tutorials in our developer guide. You can also subscribe to our discussion forum to get launch announcements and post your questions.