Docker Images
This year in March there will be the second edition of Data Science School. The images provided in this project gives the necessary software to run the data challenges that will be presented to the attendees.
The images can be downloaded directly from Docker Hub. In Docker Hub we provide multiple tags that present different software combinations, such as:
| Tag | Image details | Python Version | Base Image |
|---|---|---|---|
| cpu-py35-jnote-gwpy | Keras, Tensorflow, GWPY | 3.5 | Datmo |
| cpu-py36-keras_tutorial | Keras | 3.6 | python3.6 |
Details about using this images can be found on use docker or use udocker pages.
To download this docker images from official Docker Hub project page just select the desired tag and run the following command:
docker pull lipcomputing/data_science_school_2019:<tag>
where <tag> is one of the mentioned tags in above table.
All notebooks and data sets are already available inside images in /notebooks and /notebooks/data respectively.
References
All images include Jupyter Notebook that provides a web-based application suitable for capturing the whole computation process: developing, documenting, and executing code, as well as communicating the results.
The base image Datmo provide several workspaces configured with necessary software for each production model that data scientists need. They implemented some useful concepts that allow better integration for each environment. They also implemented run concept comprised of tasks and snapshots.
Datmo also provides docker image with already preconfigured datmo workspaces and environments. For Data Science School we are using already generated docker image as base images:
- datmo/keras-tensorflow:cpu-py35-notebook
For more details about Datmo image features review their README.
The guide to setup the necessary environment is available on Datmo DOCS.
For additional parameters and configurations to Jupyter notebook just check the available documentation.