Collaboration tools
for ML teams
Experiment tracking, model governance, collaboration
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Manage teams of remote machine learning practitioners. See everyone’s machine learning experiments in a central place. Make onboarding and switching between projects seamless with a unified history of all experiments your team has run.

Here's an interview with Peter Welinder and his robotics team at OpenAI on how they use Weights & Biases.
Read the full interview with Peter Welinder from OpenAI ➞
If you'd like to see our tools in action, here are some quick links to our docs and a live example of a W&B project.
Features
Shared reports
Use W&B to keep track of progress on projects. Organize, visualize, and describe your work in a stable record that’s accessible to your team and your future self.
Team Dashboard
Collaborate in a central repository. The dashboard is a single, live-updating page that shows every project, experiment, and report.
Catch Regressions
We keep a record of every change to your model, so when a team member pushes an update you can immediately spot regressions.
Massively scalable
We work with some of the largest machine learning teams in the world, and our product is built to scale to millions of experiments. We natively support distributed training.
Benchmark model performance
Decide on criteria, visualize performance, and customize queries to compare your model variants and focus on the right ones.
System of record
Track everything in one place. W&B automatically logs every input into your training for regulatory compliance and reproducibility.
In 5 minutes, get seamless tracking
for every project.
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