Things to understand:
- Code: where is it, version control, what scripts are relevant to which part of the pipeline (data gathering + preprocessing, model training, prediction)
- Model: architecture (and alternatives considered / rejected), features being used (or explicitly not used)
- Documentation: where it lives
- Future work: what improvements are prioritized right now
- ... (please add if I missed anything)