Automated ML Pipelines
Automates end-to-end machine learning pipelines including data processing, training, testing, and deployment with CI/CD integration.
Function Hub
Provides a repository of pre-built functions for ETL, auto-training (e.g., Scikit-Learn, XGBoost), batch inference, and Azure AutoML.
Real-Time Model Serving
Supports real-time model serving via Nuclio serverless functions running on Kubernetes or Docker environments.
Experiment and Metadata Tracking
Automatically tracks data lineage, experiments, models, and metadata with a user interface for viewing projects and runs.
Scalable Resource Management
Manages scalable resources such as virtual machines, containers, and GPUs for distributed processing and auto-scaling.