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JupyterLab over a Tensorflow

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 Python3 language. Python 2 version here

Be aware! You should read carefully the usage documentation of every tool!

Details

Docker Hub Docker Pulls Docker Stars Docker Build Size/Layers
tf-jupyterlab

This image is the base image for a set of images Data Science Docker Stacks

Build Instructions

Build Python3 flavour for amd64 or armv7l architecture (thanks to its Multi-Arch base image)

docker build -t elswork/tf-jupyterlab:latest .

My Real Usage Example

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:latest

If you want to use a version that include OpenCV you can use this:

docker run -d -p 8888:8888 elswork/tf-jupyterlab:latest_ocv

A more complex sample:

docker run -d -p 8888:8888 -p 0.0.0.0:6006:6006 \
 --restart=unless-stopped elswork/tf-jupyterlab:latest

Point 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_name

With the second example you can run TensorBoard executing this command in the container:

tensorboard --logdir=path/to/log-directory --host=0.0.0.0

And pointing your browser to http://localhost:6006