In this video, you’ll learn how models are trained, evaluated, developed, and deployed and how you can use wandb at each step of that lifecycle to help build better performing models faster.
We’ll use a computer vision model as our guide here, but this demo is use case agnostic. It’s meant to give you a deeper understanding of the broad feature set wandb comes with out of the box. Here’s what we cover in the video:
⏳ Timestamps:
0:00 Introduction
0:18 The life cycle of a typical machine learning model
3:27 How W&B works with your code
4:23 Demo: Navigating the W&B Workspace and Experiment Tracking
6:20 Demo: Using W&B Launch to automate jobs
7:44 Demo: Managing serialized data with W&B Artifacts
9:10 Demo: Organizing and understanding models with W&B Model Registry
12:18 Demo: Leveraging W&B Reports for knowledge transfer
14:30 - Parting thoughts
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