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Log and track ML metrics, parameters, models with Git and DVC

7 pointsby shchekleinalmost 2 years ago

1 comment

londogardalmost 2 years ago
I really enjoy using DVC. I do have some drawbacks compared to other offering like MLFlow and W&amp;B.<p>1. Harder to track experiments on remote VM&#x27;s (e.g. Azure) as there&#x27;s no server (we need to feed results back somehow) 2. Impossible (?) to track different types of experiments in the same repo. MLFlow has a way to define experiments and runs, which means I can easily group Regression vs Classification or even if I try a completely different task with the same data.<p>If anyone has a good suggestion on how to solve these two I&#x27;d love to fully commit to DVC!
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