MLOps using GitHub

There are many moving parts of an ML App, including data, model and teams, and effective tracking of all of these parts is a critical component of ML Lifecycle. As our ecosystem becomes complex, deploying ML Apps gets significantly harder, which reduces performance. In this session, we will look at how we can use GitHub as the center of our MLOps Lifecycle to bind our data, model, and our teams.