What are the differences between DVC and Git LFS?

What are the differences between DVC and Git LFS?

DVC (Data Version Control) is designed for managing data and machine learning models, while Git LFS (Large File Storage) is used to handle large files in Git repositories. DVC provides features like data pipelines and reproducibility, whereas Git LFS focuses on storing large files efficiently.

Can you explain how DVC handles data pipelines?

DVC allows you to define data pipelines using a simple YAML configuration. You can specify stages, dependencies, and commands to run, making it easy to track changes and reproduce results.

Is DVC suitable for collaborative projects?

Yes, DVC is great for collaboration. It integrates with Git, allowing team members to share data and models easily while maintaining version control.

What are some use cases for Git LFS?

Git LFS is ideal for projects that involve large binary files, such as images, videos, or datasets, where traditional Git would struggle with performance.

Which one should I choose for my machine learning project?

If your project heavily involves data and model management, DVC is likely the better choice. If you just need to manage large files alongside code, Git LFS might suffice.