Weights & Biases

What this tool can do

Weights & Biases provides tools for managing machine-learning experiments, tracking model performance and organizing datasets in a reproducible way. It integrates with major ML frameworks and supports collaboration across data science teams. The platform helps visualize training runs, compare model versions and detect issues early. It also enables production monitoring to ensure deployed models perform reliably over time.

Typical Use Cases

Experiment tracking and comparison
W&B logs training runs, metrics and hyperparameters, allowing teams to compare model versions efficiently.

Model performance visualization
The platform visualizes learning curves, predictions and artifacts to support clearer analysis.

Dataset and artifact management
Users can version datasets and store generated artifacts to maintain reproducible ML pipelines.

Model lifecycle documentation
W&B helps document workflows, decisions and parameters for long-term traceability.

Model monitoring in production
The tool alerts teams to performance drifts and issues in deployed models.

Collaboration across ML teams
Multiple users can share dashboards, insights and experiments within shared workspaces.