W&B Advanced: Introduction
Go beyond basic experiment tracking. Learn the advanced W&B features that power ML teams at scale.
Beyond Experiment Tracking
The W&B Basics course covered experiment tracking, basic sweeps, and artifacts. This advanced course dives into the features that make W&B a complete ML platform for teams.
What We'll Cover
Reports
Interactive documents that combine live visualizations, tables, and markdown. Share experiment findings with stakeholders, create reproducible analyses, and build team knowledge bases.
Tables
Log structured data for deep analysis. Compare model predictions side-by-side, visualize dataset distributions, and build interactive data exploration workflows.
Advanced Sweeps
Multi-objective optimization, early termination strategies, distributed sweeps across clusters, and custom sweep agents for complex search spaces.
Launch
Submit and manage training jobs across any compute backend - Kubernetes, AWS SageMaker, GCP Vertex AI, or local Docker containers.
Who Is This For?
ML Engineers in teams
Who need to communicate results, coordinate experiments, and manage shared compute resources.
Data Scientists scaling up
Moving from notebooks to production workflows with proper experiment management and reproducibility.
ML Platform Engineers
Building internal ML platforms and need to integrate W&B into CI/CD pipelines and compute infrastructure.
wandb.init(), wandb.log(), and the W&B dashboard.Ready to Go Deeper?
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