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Last pushed: a year ago
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Machine learning projects
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Start CPU only container

$ docker run -it -p 8888:8888 saphc/ml:initial

By defualt jupyter should be running, but if that is not the case then: Run /run_jupyter.sh inside the container.

Go to your browser on http://localhost:8888/

NOTE: Using tags: v01-python27 and v01-python35 will get you a docker image that has anaconda and virtualenvwrapper installed.

Start GPU (CUDA) container (Not supported yet)

$ export CUDA_SO=$(\ls /usr/lib/x86_64-linux-gnu/libcuda | xargs -I{} echo '-v {}:{}')
$ export DEVICES=$(\ls /dev/nvidia
| xargs -I{} echo '--device {}:{}')
$ docker run -it -p 8888:8888 $CUDA_SO $DEVICES tensorflow/tensorflow-devel-gpu
Start /run_jupyter.sh inside the container.
Go to your browser on http://localhost:8888/

For more details details see
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/docker/README.md

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saphc

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