AI engineering glossary · MLOps, LLMOps cloud
What is MLflow?
MLflow: An open-source platform for managing the machine learning lifecycle. It records experiments with parameters and metrics, stores model artefacts, provides a model registry and offers a standard format for packaging and serving models.
MLflow: an example
A data scientist logs 30 training runs with `mlflow.log_metric("auc", 0.91)` and compares them in a web interface.
Related terms
- Experiment tracking
- Model registry
- Model artefact
- Weights & Biases
More MLOps, LLMOps cloud terms
- MLOps
- Model artefact
- Model monitoring
- Model promotion
- Model registry
- Model validation
- Model versioning
- Monitoring
Where you learn it
MLflow is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.