Experiment Tracking
Automatically log hyperparameters, metrics, and system metrics during training to visualize and compare runs in an interactive dashboard.
Model Monitoring
Monitor deployed models in production to detect data drift, performance degradation, and anomalies with real-time alerts.
Dataset Versioning
Track and version datasets to ensure reproducibility and enable easy rollback or comparison between dataset versions.
Collaborative Reports
Create and share interactive reports and dashboards to communicate experiment results and insights across teams.
Hyperparameter Sweeps
Run and manage hyperparameter optimization sweeps to automatically find the best model configurations.
Integrations
Supports integration with popular ML frameworks like TensorFlow, PyTorch, Keras, and cloud platforms such as AWS, GCP, and Azure.