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!
We'll be using:
Git & GitHub
Free Google Drive storage
DVC
Resources:
Code: https://github.com/elleobrien/mlops_t...
DVC "Getting Started" docs: https://dvc.org/doc/start
Questions? Comments? Let us know! We'll do our best to answer any technical questions.
🧑🏽💻 To learn more. about our tools, take our free online course at https://learn.iterative.ai
On this page of the site you can watch the video online MLOps Tutorial #2: When data is too big for Git with a duration of hours minute second in good quality, which was uploaded by the user DVCorg 06 August 2020, share the link with friends and acquaintances, this video has already been watched 22,983 times on youtube and it was liked by 533 viewers. Enjoy your viewing!
