🦉DVC

@DVCorg

Open source tool for data, models, & experiment versioning for ML projects. Join our stellar community dvc.org/support for help, support and insights.

San Francisco, CA

dvc.org

Replies Reposts Media Articles

🦉DVC
@DVCorg
Sep 3
Dr. Aleena Baby turns the classic 47-files-in-one-folder ML mess into a professional project layout: configs, src, tests, CI/CD workflows, MLflow tracking, and .dvc files for data. A one-weekend cleanup for reproducibility. 👉🏽 hubs.la/Q04tN6wj0
🦉DVC
@DVCorg
Sep 1
New research: Buhayh, McKinnie, Canel & Burke simulate 4 profile-portability scenarios across Amazon, Goodreads & MovieLens, using DVC for reproducibility. What happens to your recommender data when you switch algorithms? 👉🏽 hubs.la/Q04tKBmf0
🦉DVC
@DVCorg
Aug 31
AWS featured DVC in an official ML lineage pattern alongside SageMaker AI and MLflow. Join the team who built it for a live walkthrough on Sept 22!
DVC + SageMaker + MLflow: End-to-End Lineage Webinar
From dvc.org
🦉DVC
@DVCorg
Aug 26
New research: Madugula & Esteva de la Rosa invert the Kelly Criterion to price DeFi loan risk, with MLflow tracking and DVC + DagsHub versioning RWA data for reproducibility. A Reverse Kelly AMM for risk-adjusted lending. 👉🏽 hubs.la/Q04tMBfG0
🦉DVC
@DVCorg
Aug 24
Three pillars of modern MLOps, one clear framework: data versioning with DVC as the gold standard, experiment tracking (MLflow, W&B, ClearML), and metadata/lineage management. The shift from ad-hoc ML to deterministic engineering. 👉🏽 hubs.la/Q04tM9FT0