[D] Effective Management of your Machine Learning Laboratory
The author shortly demonstrate how you can easily make use of DVC tool to effectively manage your ML workflow: Effective Management of your Machine Learning Laboratory
An example project (from the article) in the author’s personal GitHub
The following common ML workflow issues are dealt with in the article:
- how to connect versions of source codes and versions of large data files?
- how to recover model from weeks earlier without retraining it?
- how to run only model inferencing using a model that I built weeks ago?
- how to keep a track of model parameters of various ML experiments?