Use MLflow to track experiments in Azure Databricks
When you run data science and machine learning experiments at scale, you can use MLflow to track experiment runs and metrics.
After completing this module, you will be able to:
- Understand capabilities of MLflow
- Use MLflow terminology
- Run experiments
Before starting this module, you should be familiar with using Python to train machine learning models in Azure Databricks.
Run experiments min
Knowledge check min