AWS-Optimized Kubeflow Notebooks
Installing Kubeflow on AWS includes AWS-optimized container images as default options for a Kubeflow Jupyter Notebook server. For more information on gettings started with Kubeflow Notebooks, see the Quickstart Guide.
AWS-optimized container images
The following container images are available from the Amazon Elastic Container Registry (Amazon ECR).
public.ecr.aws/c9e4w0g3/notebook-servers/jupyter-tensorflow:2.6.0-gpu-py38-cu112 public.ecr.aws/c9e4w0g3/notebook-servers/jupyter-tensorflow:2.6.0-cpu-py38 public.ecr.aws/c9e4w0g3/notebook-servers/jupyter-pytorch:1.9.0-gpu-py38-cu111 public.ecr.aws/c9e4w0g3/notebook-servers/jupyter-pytorch:1.9.0-cpu-py38
These images are based on AWS Deep Learning Containers. AWS Deep Learning Containers provide optimized environments with popular machine learning frameworks such as TensorFlow and PyTorch, and are available in the Amazon ECR. For more information on AWS Deep Learning Container options, see Available Deep Learning Containers Images.
Along with specific machine learning frameworks, these container images have additional pre-installed packages:
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