Data Versioning: Towards Reproducibility in Machine Learning - Nicolás Eiris - TryoLabs

Nicolás Eiris, Machine Learning Engineer at Tryolabs, presents the "Data Versioning: Towards Reproducibility in Machine Learning" tutorial at the May 2022 Embedded Vision Summit.

Surprisingly in 2022, reproducibility is still a big pain point in most data science workflows. A critical element required for reproducibility is version control. Unfortunately, in machine learning there is a notorious lack of standards for version control, so developers typically resort to crafting ad-hoc workflows. And frequently, developers reinvent the wheel due to a lack of awareness of existing solutions.

In this talk, Eiris introduces DVC, short for “Data Version Control,” an open-source tool that Tryolabs has found can significantly alleviate the pain of reproducibility in data science workflows. He covers the motivation for such a tool, digs into its main features and will hopefully convince you that your life will be much better if you integrate it into your next project. Everything is illustrated through a real-world example of an end-to-end ML pipeline.

See more from the Embeded Vision Summit here:    / @edgeaivision  
And learn about the conference here: https://embeddedvisionsummit.com/

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📌 START LEARNING DVC
• 📘 Docs: https://dvc.org/doc
• 🎓 Free Online Course: https://learn.dvc.org
• 💻 VS Code Extension: https://marketplace.visualstudio.com/...
• 📺 Subscribe to our channel:    / @dvcorg8370  

💬 LET'S CONNECT
• GitHub: https://github.com/iterative/dvc
• Discord Community: https://dvc.org/chat
• Twitter/X:   / dvcorg  
• LinkedIn:   / iterative-ai  

👇 COMMENT: What part of DVC would you like us to cover next?

#DataVersionControl #MLOps #MachineLearning #ReproducibleML #DVC