Environment¶
To get the most out of MyAutoML you will need to install and setup several components in your environment for MyAutoML to work with. Please have a look at the Machine Learning Process to see where these components fit in.
Model Registry: MLflow¶
As a model registry we work with MLflow. MLflow has two separate modules helping us to keep a good record of our models:
MLflow Tracking
MLflow Model Registry
In the Machine Learning Process, when we refer to a Model Registry, we mean both of these MLflow components above: every trained model is tracked in the MLflow Tracking Server. Additionally, some will be registered with a registered model name in the MLflow Model Registry. In the prediction process, a model is loaded from the MLflow Model Registry.
Please refer to the installation instructions and MLflow Tracking Servers to get you started. In order to use the MLflow Model Registry, you will need to setup an MLflow Tracking Server with a database Backend Store, such as SQLite or PostgreSQL.