Skip to content

Versioning Strategies for Data Science & ML Projects

Versioning Strategies for Data Science & ML Projects

I presented my research on Data Version Control (DVC) at the Experts Meetup hosted by the Cloud Centre of Excellence at Vodafone Germany's Düsseldorf campus. The paper covers versioning strategies tailored for Data Science and ML projects, with a focus on reproducibility and collaborative workflows.

Explore the Code

The presentation included live demonstrations and hands-on exercises covering key data versioning concepts.

Check out the GitHub repository for the demo code and full tutorial.

Topics Covered in My Research Paper

Understanding Versioning

  • Introduction to Versioning: Exploring the basics and significance of version control.
  • Evolution of Versioning Practices: How versioning has evolved in the data science landscape.
  • Benefits and Limitations of Git: Analyzing what Git offers and where it falls short for data projects.
  • Data Version Control with DVC: Introducing DVC as a solution for data-centric versioning.
  • Integrating Git and DVC: Combining the strengths of Git and DVC for an optimized workflow.

DVC Fundamentals

  • Initializing a DVC Repository: Step-by-step guide to setting up DVC in your project.
  • Adding Data to DVC: Best practices for incorporating data files into DVC.
  • Comparing DVC with Git: Understanding the differences and when to use each tool.

Essential DVC Commands

  • dvc get: Retrieve files from a remote repository effortlessly.
  • dvc add & dvc commit: Efficiently add and commit data files to DVC.
  • dvc remote: Configure and manage remote storage options with DVC.
  • dvc push: Seamlessly push your data to remote storage.
  • Tracking Data Files with DVC: Keeping a robust record of your data files.

Advanced DVC Features

  • DVC Pipelines: Creating and managing comprehensive data pipelines.
  • Experiment Tracking: Monitoring experiments with varying data, code, and models.
  • Metrics & Plots: Visualizing model performance through detailed metrics and plots.

For questions or discussion on versioning strategies, reach out on LinkedIn or email contact@kunal-pathak.com.