Code and Data in a large Machine Learning project
Read OriginalThe article details the challenges and solutions from a large machine learning project involving multiple data scientists and engineers. It focuses on organizing code and data across different machines, using R package structures for reproducibility, managing model versions, and implementing a simple multi-user code folder system on a shared server for parallel development.
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