Reproducible ML Experimentation with DVC and VS Code
Abstract
Discover the power of Data Version Control (DVC) and its integration with VS Code via the DVC Extension in this talk. We will introduce DVC’s core features, including data versioning, pipeline management, and model tracking, and demonstrate how it enhances collaboration and reproducibility in ML projects. Next, we will explore the DVC Extension for VS Code, which offers a user-friendly interface for managing DVC projects within the code editor. Learn how to visualize, reproduce and compare experiments easily. By the end of the session, attendees will be equipped to streamline their ML workflows and ensure reproducibility in their projects.
Alexander Kim
MLOps Engineer - Iterative.ai
Alex Kim is an MLOps Engineer. His background is in physics, software engineering, and machine learning. In the last few years, he became increasingly interested in the engineering side of ML projects, processes and tools, needed to go from an idea to a production solution. He occasionally teaches online courses on the topics of Data Science, Machine Learning, and MLOps.