Managing the ML Model
Understand how to use MLflow within Azure Machine Learning to manage the ML lifecycle. Learn to log model parameters, custom metrics, and artifacts, view experiment data, and save models for easy deployment without extra scripting or environment setup.
We'll cover the following...
We'll cover the following...
MLflow integration
In this lesson, we will learn about using MLflow models.
MLflow is an open-source platform for managing the ML lifecycle. Azure Machine Learning is integrated with MLflow. Therefore, we can save the models in MLflow format, track the models using MLflow URI, and log the metrics and artifacts.
Running an MLflow job
Let’s run a simple job to learn about three important use cases for MLflow integration.