MLRun basics

• What is MLRun?
• MLOps development workflow
• Installation and setup guide
• Tutorials and examples

Concepts

• Projects
• Data and artifacts
• Functions
• Functions Marketplace
• Jobs
• Feature store
• Model training
• Real-time serving pipelines (graphs)
• Model serving
• Workflows
• Model monitoring
• CI/CD and automation

Data collection and preparation

• Data stores
• Ingesting data
• Logging datasets
• Feature store: data ingestion

Training

• Create a basic training job
• Working with data and model artifacts
• Automated experiment tracking
• Using the built-in training function
• Training with the Feature Store
• Hyperparameter tuning optimization
• CI/CD, rolling upgrades, git

Model serving

• Basic model serving class
• Test and deploy a model server
• Using built-in model serving classes
• Model serving graph
• Serving with the feature store
• Canary deployment
• Model serving API

Continuous Monitoring and Retraining

• Model monitoring (beta)
• Workflows

References

• API index
• API by module
• Command-Line Interface (Tech preview)
• Glossary