MLOps Tutorial #2: When Data Is Too Big for Git

MLOps Tutorial #2: When Data Is Too Big for Git

Git is a core part of DevOps and continuous integration, but making it work with machine-learning-sized datasets can be challenging. This hands-on tutorial shows you how to use Git version control with a machine learning project even when your dataset is too big for GitHub. We'll focus on setting up a remote data repository and using Git + DVC to push from your computer, to external storage, and anywhere else it needs to go!

Git is a core part of DevOps and continuous integration, but making it work with machine-learning-sized datasets can be challenging. This hands-on tutorial shows you how to use Git version control with a machine learning project even when your dataset is too big for GitHub. We'll focus on setting up a remote data repository and using Git + DVC to push from your computer, to external storage, and anywhere else it needs to go!

We'll be using:

  • Git & GitHub
  • Free Google Drive storage
  • DVC

Resources:

mlops git machine-learning

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