Applying GitOps Principles at Every Step of an E2E MLOps Project - A Workshop

With the emergence of IaC (infrastructure as code) tools, we have seen GitOps become an increasingly popular DevOps pattern that facilitates automation, reproducibility, and security. While hugely beneficial, applying the same principles in MLOps is not straightforward due to the specific aspects of the field such as the need to work with large amounts of data and the experimental nature of ML development. In this workshop, Tibor Mach will shows how we can bridge these gaps by using tools such as DVC. Step by step, he'll help you create an end-to-end MLOps pipeline that is centered around the Git repository as its single source of truth. *What You’ll Learn:* In this largely interactive workshop, you can learn how you can use your git repositories to keep track of your ML experiments, version data and models, maintain a model registry, and handle model deployment *Prerequisite Knowledge:* Basics of working with Git and conceptual understanding of GitHub Actions or GitLab CI. *Repo* https://github.com/iterative/workshop... *Slides* https://docs.google.com/presentation/... 📌 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