Experiment Tracking for Data Science Teams
Logging parameters, metrics, and artifacts during model training to monitor performance and reproducibility.
Model Packaging and Deployment
Packaging machine learning models with code and dependencies for deployment as APIs or batch jobs.
AI Application Observability
Using tracing APIs and dashboards to debug notebooks and monitor AI applications in production.