MLflow Tracking Quickstart Notebook

Welcome to the MLflow Tracking Quickstart! The notebook-based companion to the quickstart guide is tailored to help you quickly understand the core features of MLflow Tracking. In just a few minutes, you’ll gain hands-on experience with the fundamental aspects of MLflow, including:

• Installing MLflow.

• Starting a local MLflow Tracking Server.

• Logging and registering a model with MLflow.

• Loading a logged model for inference using MLflow’s pyfunc flavor.

• Viewing the experiment results in the MLflow UI.

If you are new to MLflow, we recommend starting with this quickstart to familiarize yourself with the most commonly used MLflow APIs before diving into more detailed tutorials.

MLflow Tracking Quickstart Guide

Learn the basics of MLflow Tracking in a fast-paced guide with a focus on seeing your first model in the MLflow UI