Welcome to the Comet Docs!
Get started with two lines of code¶
1 2 3 4 5 6 7 8 9 10 11 12 |
|
Build Better Models Faster
Comet’s machine learning platform tracks the lifecycle of a model in one user interface, so you can build, collaborate, and iterate faster. For enterprise, bring Comet to what you build; we treat virtual private cloud (VPC) and on-premises environments as first-class citizens.
Try Comet freeDiscover Comet
Track models and training runs
Start managing experiments using the tools, libraries, and frameworks you use today.
Custom visualizations for faster iteration
Iterate, debug, and evaluate models faster with custom visualizations you can build yourself or choose from our library of templates.
Reproduce experiments
Create dataset versions and track hyperparameters for faster and easier reproducibility and collaboration.
Model Registry
Save model versions and deploy registered models using your computing environment.
New at doc
Configure webhooks when a model is deployed to development, staging or production in order to trigger a CI/CD pipeline.
The Kubeflow integration allows you to track the status of the DAG and individual steps straight from the Comet UI.
Combine GitLab's powerful CI/CD pipelines and Comet’s Experiment Management capabilities to create a powerful model development workflow.
Popular
Comet provides a self-hosted and cloud-based machine learning platform that allows data science teams to track, compare, explain their experiments and models.
Strat tracking your training runs by adding a couple of lines of code at the beginning of your training script.
Comet integrates with most machine libraries to automatically log hyper-parameters, metrics, code and more.