AI engineering glossary · MLOps, LLMOps cloud
What is CT (continuous training)?
Continuous training (also called CT): Automatically retraining a model on a schedule or when triggers fire, such as new data arriving or measured performance dropping, and then validating and releasing it through the same pipeline. It keeps models current as the world changes.
Continuous training: an example
A recommender retrains every night on the day's clicks, and is promoted only if it beats the current model on held-out data.
Related terms
- MLOps
- Data drift
- ML pipeline
- Model registry
More MLOps, LLMOps cloud terms
- Data versioning
- Dependency pinning
- Deployment pipeline
- Disaster recovery
- Distributed tracing
- Docker
- Docker Compose
- Docker container
Where you learn it
Continuous training is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.