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In ML projects hard links and symbolic links can help us, when setting up new experiments, to rearrange data files quickly and efficiently. However, with traditional links, we run the risk of polluting the data files with erroneous edits.
The article explain details of using links, some cool new stuff in modern file systems (reflinks), and an example of how DVC (Data Version Control) tool leverages this for managing ML project datasets and workflow: Reflinks vs symlinks vs hard links, and how they can help machine learning projects
submitted by /u/cmstrump
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