I really like the analogy of git as the 'assembly language' for version control.
From a quantitative developer perspective (ML, AI, and data science), one of the biggest issues with managing version control with conventional repo platforms (GitHub, Bitbucket, etc) is that they track code properly, but not other mission-critical development properties that currently need to be managed manually (package/lang versions, model configuration).
While something could be built on top of one of these platforms to augment the features that already exist, we see going straight to git itself to be the best solution for building a more all-encompassing tracking system that works for developers in our domain.
Would love to hear more perspectives from people in the machine learning, data science, and artificial intelligence spaces, as my company Datmo, is building a CLI tool and web platform that tries to solve these issues!
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