Demystifying Docker for Data Scientists by Shaheen
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If you are a Data Scientist, you must have been hearing a lot about docker and how it is the hottest thing to have ever happened! If you are wondering what the fuss is all about and how you can leverage it for your data science work and especially for deep learning projects, you have stumbled on the right presentation.
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Demystifying Docker for Data Scientists by Shaheen
3. • Packaging the application into 'Containers’.
• Instead of running the code we run the Container.
• Application code, the libraries and dependencies needed
to run the application
• Portable, self sufficient, run anywhere
11. ~$ docker pull microsoft/cntk # This will get the latest image, which today
means latest available GPU runtime configuration.
~$ docker pull microsoft/cntk:2.1-cpu-python3.5 # To get a specific
configuration you need to add a tag. This will get you CNTK 2.1 CPU runtime
configuration set up for Python 3.5.
~$docker images
REPOSITORY TAG IMAGE ID
CREATED SIZE
microsoft/cntk 2.1-cpu-python3.5 57f6b9f1b27c 2
months ago 6.74GB
28. ~$ docker pull tensorflow/tensorflow # This will get the latest image
for CPU only container
~$ docker pull tensorflow/tensorflow:latest-gpu # This will get
the latest image for GPU (CUDA) container (Install nvidia-docker)
~$docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
tensorflow/tensorflow latest a61a91cc0d1b 3 weeks ago
1.25GB
microsoft/cntk 2.2-cpu-python3.5 57f6b9f1b27c 2 months ago
6.74GB