Version control for data science and machine learning with DVC

Data version control (DVC) is an open source tool that brings all the versioning and collaboration capabilities you use on your code with Git to your data and machine learning workflow.

If you use datasets in your work, it makes it easy to track their evolution.

If you are in the field of machine learning, it additionally allows you to track your models, manage your pipelines from parameters to metrics, collaborate on your experiments, and integrate with the continuous integration tool for machine learning projects CML.

This webinar will show you how to get started with DVC, first in the simple case where you just want to put your data under version control, then in the more complex situation where you want to manage your machine learning workflow in a more organized and reproducible fashion.

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