Getting Started with Registry from Weights & Biases

Explore the powerful features of Registry, a curated central repository for storing and managing ML models and datasets. Learn how to log artifacts, publish and share models, and utilize versioning, aliases, lineage tracking, and governance tools. Discover the process of logging models in Weights & Biases, managing artifact metadata, and navigating the Registry interface. Gain insights into Registry settings, access control, and creating custom registries. Follow along as the video demonstrates publishing models and datasets to specific registries, empowering you to efficiently organize and share your machine learning assets.

Syllabus

Registry Introduction
Definition of Registry
Logging a model in W&B
Managing artifacts and their metadata
Registry quick tour
Registry settings and access control
Creating a custom registry
Publishing a model to a custom registry
Publishing a dataset to the dataset registry