It is an open source platform for tracking machine learning experiments.
A machine learning experiment are those activities that are taken when building a model.
This involves data loading, preprocessing, transformation, model parameters, duration of model training, the model
itself, etc.
In order to keep track of these details, it's a better practice to use tools like mlflow.
The notes below could be a guide on how to get started with mlflow in your Jupyter Notebooks. It covers saving to mlflow and collecting stored artifacts from mlflow