How Comet can streamline machine learning on The GitLab DevOps Platform

What this post added

This post details a workflow for integrating external ML experiment tracking tools (Comet) with GitLab CI/CD. It demonstrates how to set up separate GitLab projects for ML model training and application code, and how to use CI/CD pipelines to automate model training, evaluation, publishing of metrics to merge requests, and registering approved models to Comet's Model Registry. It also outlines the pipeline configuration for these steps, including the use of Python images, artifact storage, and manual deployment triggers.