DEPRECATION: Python 2.7 will reach the end of its life on January 1st, 2020. Please upgrade your Python as Python 2.7 won't be maintained after that date. A future version of pip will drop support for Python 2.7.
A Docker file to build images for AMD & ARM devices over a base image based with a minimal installation of Tensorflow an open source software library for numerical computation using data flow graphs. Over this base will be installed JupyterLab an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Computational Narratives as the Engine of Collaborative Data Science. All this under Python 2 language. Python 3 version here.
Be aware! You should read carefully the usage documentation of every tool!
| Docker Hub | Docker Pulls | Docker Stars | Docker Build | Size/Layers |
|---|---|---|---|---|
| tf-jupyterlab-py2 |  |
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This image is the base image for a set of images Data Science Docker Stacks
Build Python2 flavour for amd64 or arm32v7 architecture (thanks to its Multi-Arch base image)
docker build -t elswork/tf-jupyterlab-py2:latest .In order everyone could take full advantages of the usage of this docker container, I'll describe my own real usage setup.
docker run -d -p 8888:8888 elswork/tf-jupyterlab-py2:latestA more complex sample:
docker run -d -p 8888:8888 -p 0.0.0.0:6006:6006 \
--restart=unless-stopped elswork/tf-jupyterlab-py2:latestPoint your browser to http://localhost:8888
First time you open it, you should provide a Token to log on you cand find it with this command:
docker logs container_nameWith the second example you can run TensorBoard executing this command in the container:
tensorboard --logdir=path/to/log-directory --host=0.0.0.0And pointing your browser to http://localhost:6006