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| Name | Machine Learning Experiment Tracking with VS Code, Git, and DVC |
| Video Uploader | Video From DVCorg |
| Upload Date | This Video Uploaded At 26-07-2023 19:00:04 |
| Video Discription | Dmitry Petrov, creator of DVC, provides a history of machine learning experiment tracking tools and how and why experiment tracking can be done with VS Code, Git and DVC to provide truly reproducible data science for ML teams. In this session from the HighLoad Conference in December 2022, Dmitry teaches: 1. The importance of experiment tracking 2. How to leverage the tools you already use for machine learning: VS Code and Git This system improves the development experience by keeping everything in the IDE and reducing the number of moving parts in your ML infrastructure. *Try out the DVC Extension for VS Code here:* https://marketplace.visualstudio.com/items?itemName=Iterative.dvc To learn more about Iterative's open-source and SaaS tools please visit: 🧑🏽💻 *Our free online course:* https://learn.iterative.ai ✍🏼 *Our docs:* https://dvc.org/doc (Data Version Control, Pipelines, Experiments) https://cml.dev/doc (CI/CD for Machine Learning) https://mlem.ai/doc (Package and Serve your models) https://studio.iterative.ai (Team Collaboration, Experiments, Model Registry) *Join the Community on our Discord server:* https://discord.gg/W49xzNmycw For more information on the HighLoad Conference: https://highload.rs/2023/ #dvc #machinelearning #datascience #generativeai apzgh_Up6gs |
| Category | Science & Technology |
| Tags | Data Version Control | VS Code | Git | GitOps | MLOps | Machine Learning experiment tracking | DVC | Sacred | history of ML experiment tracking | DVC Extension for VS Code | reproducibility | reproducibility in machine learning | reproducibility in data science | machine learning experimentation | machine learning experiment management | machine learning experiment tracking tools | data version control software | data science version control | reproducible research |
