https://github.com/albarji/teachingcontainer

A Docker container I use for my lectures
https://github.com/albarji/teachingcontainer

docker keras machine-learning scikit-learn

Last synced: 2 months ago
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A Docker container I use for my lectures

• Host: GitHub
• URL: https://github.com/albarji/teachingcontainer
• Owner: albarji
• License: mit
• Created: 2017-04-15T14:24:19.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2017-04-16T16:25:41.000Z (about 9 years ago)
• Last Synced: 2025-02-09T10:11:20.335Z (over 1 year ago)
• Topics: docker, keras, machine-learning, scikit-learn
• Language: Makefile
• Size: 4.88 KB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Teaching Container

A Docker container I use for my machine learning lectures.

Includes

* Miniconda Python 3

* scikit-learn 0.18.1

* keras 2 with Tensorflow backend

* matplotlib and seaborn

* Jupyter notebook (launched at start)

The container is also prepared for mapping the container X11 output to that of the host, so applications with a Graphical Interface can be used.

## Prerequisites

You will need Docker Community Edition. Working under a Linux operative system is strongly recommended, but if you wish to work under Windows or Mac it might be best for you to install Docker Toolbox.

## Usage

Run

    docker run --rm -it -p 8888:8888 -v $(pwd):/home/developer -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix teaching-container

in a terminal while standing at the folder with the downloaded lab assignments. Then follow the link to the Jupyter notebook service that will appear in the terminal.