Build an ML app pipeline with GitLab Model Registry using MLflow

This tutorial guides you through setting up an MLOps pipeline using GitLab Model Registry and MLflow. It explains the importance of MLOps in managing and automating machine learning models' lifecycle, highlighting GitLab's features like version control, CI/CD pipelines, and collaboration tools. The tutorial includes instructions for setting up environment variables, training and logging models, registering successful candidates, and deploying an ML app using Docker.