AWS Deep Learning Containers
#213 · Level 3 · Modern architecture · AI and machine learningConcept
Section titled “Concept”AWS Deep Learning Containers are container images with ML frameworks already installed. A container is a box that packs an app together with all the software it needs, and it runs the same way anywhere. These come with frameworks such as PyTorch and the needed libraries installed and tested. The images are kept in Amazon ECR. You can run ML work with the same image anywhere — SageMaker AI, EKS, ECS or EC2.
Simple example
Section titled “Simple example”A packed cooking kit — open it in any kitchen and cook the same dish.
Why it’s needed
Section titled “Why it’s needed”Keeping the ML environment the same in every place is hard; containers make it easy.
Where it’s used
Section titled “Where it’s used”Training and running ML models on EKS, ECS or SageMaker.
Azure equivalent
Section titled “Azure equivalent”Azure ML curated environments
Learn more
Section titled “Learn more”For details and the latest information, see the official documentation: