- Sponsor: Win Cowger, UC Riverside - Trash Data Projects
- Meeting Times: Wednesdays at 6:30pm (Weekly Brigade Meetings)
- Open Office hours Saturdays at 3pm
- Description: Develop machine learning model to identify spectroscopy signals from training dataset (available on existing application) and return results to existing application.
- Benefit: Enhance abilities of researchers to quickly label signals and categorize materials.
- All datasets and metadata for training the model are HERE: https://osf.io/jts9d/
- Issues and discussions on specific topics can be made HERE: https://github.com/code4sac/openspecy/issues
- We prefer you use the fork-branch-pull workflow to contribute to this repo but you can also make pull requests if that is easier for you.
- Try to use tools which allow models to be exported in hd5 format because that will allow us to port between langagues.
- Feel free to code in whatever language you are familar with but towards the end of the development, we will translate the winning model into one language.
- Benchmark we want to hit is > 99% accuracy (can be hierarchical classes).
- @ mention collaborators of this repo when you have questions and we can collaborate.
- If github doesn't work for you, feel free to work in your own framework and email your code to the maintainers of this repo.