https://github.com/jeffheaton/docker-jupyter-python-r
Jupyter notebook with Python and R.
https://github.com/jeffheaton/docker-jupyter-python-r
Last synced: 8 months ago
JSON representation
Jupyter notebook with Python and R.
- Host: GitHub
- URL: https://github.com/jeffheaton/docker-jupyter-python-r
- Owner: jeffheaton
- Created: 2018-08-12T02:36:13.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2023-03-24T01:21:15.000Z (almost 3 years ago)
- Last Synced: 2025-03-31T08:51:12.863Z (9 months ago)
- Language: Jupyter Notebook
- Size: 8.79 KB
- Stars: 12
- Watchers: 2
- Forks: 2
- Open Issues: 1
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Metadata Files:
- Readme: README.md
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README
# docker-jupyter-python-r
This is a Docker image that I created to launch Jupyter notebooks that can be used in conjunction with my course and videos:
* [T81-558: Applications of Deep Learning](https://sites.wustl.edu/jeffheaton/t81-558/)
* [Heaton Research YouTube Channel](https://www.youtube.com/user/HeatonResearch)
Contains:
* TensorFlow 2.11
* PyTorch 1.13.1
* Anaconda Python 3.10
* Note: this docker image previously contained R-lang; which has not been used in my course for some time.
* Needed Python packages for my class
This docker image can be run with the following command. You should mount a local path so that your notebooks can be saved outside the Docker container.
```
docker run -it --rm --gpus all -p 8888:8888 -v [local path]:/content/mnt/ heatonresearch/jupyter-python-r
```
It is suggested that you mount a volumne to store your files. Any changes that you make to the docker container will be lost when you exit. If you wish to keep your container, then remove the --rm. See Docker command line instructions for more information on managing containers and images.
You will then access the notebook with this URL:
http://127.0.0.1:8888/?token=[your token]
You can get the token from the console output from the ```docker run``` command.