This is the docker image for Azure Machine Learning service development task, its baseImage is:
FROM tftwdockerhub/cuda_cudnn_ana_base:latest
For Azure Machine Learning service and Data Prep development:
- Azure ML core SDK: azureml-sdk
- Azure ML data prep: azureml-dataprep
- Azure ML extras: azureml-sdk[notebook, etc..]
According to the document, only notebooks, explain, automl, contrib are installed, because databricks and automl_databricks cannot be combined with other components.
- Azure ML monitoring: azureml-monitoring
- Azure CLI 2.0 for Azure credential
It is recommended to use
lsb_release -cs
in the base docker images to check the version of the OS, in this case, it is xenial, so author set this link manually.
For more information, please check:
- Azure ML core/extras SDK installation guide
- Azure ML Data Prep SDK installation guide
- Azure ML Monitoring SDK installation guide
- Azure CLI installation guide
- tftwdockerhub/azure_ml_docker_dev:latest
on dsvm-gpu virtual machines
sudo docker pull tftwdockerhub/azure_ml_docker_dev:latest
remember the target port is 8889
sudo nvidia-docker run -it -p 8889:8888 -v \<project-dir-path\>:/app tftwdockerhub/azure_ml_docker_dev:latest
In local browser, remember the target port is 8889 and the token string on CLI screen
http://\<vm-ipaddress-or-dns\>:8889/?token=21c5e12xxxxxx