Autologging¶

Autologging is a really cool MLFlow feature that allows you to automatically log metrics, parameters, and artifacts from your machine learning experiments. It simplifies the process of tracking your experiments and makes it easier to compare different runs.

To use autologging, you just need to call mlflow.autolog() at the beginning of your script. This will automatically log all the metrics, parameters, and artifacts that are generated during the execution of your script.

In [1]:

import mlflow


mlflow.autolog()

import mlflow mlflow.autolog()