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February 21, 2026 · 1 min read

How would you manage version control for a machine learning project that involves both model training and data versioning, ensuring reproducibility and collaboration across teams?

For managing version control in machine learning projects, I recommend using Git for code and DVC (Data Version Control) for handling datasets and models. This allows for tracking changes in…

debmedia

SOFTWARE_ARCHITECT // AI_ENGINEER

📅 Feb 21, 2026 ⏱ 1 min read

HW

How would you manage version control for a machine learning project that involves both model training and data versioning, ensuring reproducibility and collaboration across teams?

COVER // HOW WOULD YOU MANAGE VERSION CONTROL FOR A MACHINE LEARNING PROJECT THAT INVOLVES BOTH MODEL TRAINING AND DATA VERSIONING, ENSURING REPRODUCIBILITY AND COLLABORATION ACROSS TEAMS?

For managing version control in machine learning projects, I recommend using Git for code and DVC (Data Version Control) for handling datasets and models. This allows for tracking changes in both the codebase and the datasets efficiently, ensuring reproducibility and facilitating collaboration across teams.

collaboration data versioning git machine learning version control

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