SageMaker Containers gives you tools to create SageMaker-compatible Docker containers, and has additional tools for letting you create Frameworks (SageMaker- ...
SageMaker provides prebuilt Docker images that include deep learning framework libraries and other dependencies needed for training and inference. For a complete list of the available pre-built Docker images, see Deep Learning Containers Images.
SageMaker provides containers for its built-in algorithms and prebuilt Docker images for some of the most common machine learning frameworks, such as Apache ...
SageMaker makes extensive use of Docker containers to allow users to train and deploy algorithms. Containers allow developers and data scientists to package ...
Amazon SageMaker provides containers for its built-in algorithms and prebuilt Docker images for some of the most common machine learning frameworks, such as Apache MXNet, TensorFlow, PyTorch, and Chainer. It also supports machine learning libraries such as …
Amazon SageMaker makes extensive use of Docker containers for build and runtime tasks. SageMaker provides prebuilt Docker images for its built-in algorithms and the supported deep learning frameworks used for training and inference. Using containers, you can train machine learning algorithms and deploy models quickly and reliably at any scale.
Sagemaker uses docker containers for training and deploying machine learning algorithms to provide a consistent experience by packaging all the code and run ...
Docker uses a simple file called a Dockerfile to specify how the image is assembled. We'll see an example of that below. You can build your Docker images ...