Optimized Jupyter Notebooks on AWS
Customize Kubeflow Jupyter Notebooks
Kubeflow Notebook Images
Currently, we add AWS optimized Kubeflow Notebook Images and make them default options in notebook server.
527798164940.dkr.ecr.us-west-2.amazonaws.com/tensorflow-1.15.2-notebook-cpu:1.2.0
527798164940.dkr.ecr.us-west-2.amazonaws.com/tensorflow-1.15.2-notebook-gpu:1.2.0
527798164940.dkr.ecr.us-west-2.amazonaws.com/tensorflow-2.1.0-notebook-cpu:1.2.0
527798164940.dkr.ecr.us-west-2.amazonaws.com/tensorflow-2.1.0-notebook-gpu:1.2.0
The ECR image provides:
AWS Deep Learning Containers as base image
The reason we take AWS Deep Learning Containers as base image, is that AWS Deep Learning Containers provides optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries on AWS.
Extra pre-installed packages
- docker-client
- kubeflow-metadata
- kfp
- kfserving
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Last modified 20.04.2021: Apply Docs Restructure to `v1.2-branch` = update `v1.2-branch` to current `master` v2 (#2612) (4e2602bd)