[D] Reproducibility in ML research and development
There has been a push to have more reproducible code that one submits to conferences like ICML, NeurIPS, etc given the call that was made for this at NeurIPS 2018 and from the wider ML community. And in general in working on projects that span several months and different developer and data science teams.
I’ve looked into tools like Pachyderm https://www.pachyderm.io/ and DVC https://dvc.org/ (I’ve found them to be a bit heavyweight in terms of setup, especially for some of my colleagues who come from more of a research and less of a software engineering background/experience)
Are there any other tools that you use to achieve this for your research and development? Would be great to mention pros and cons of each.