Monitoring in MLOPS: Reflections on Module 5 of the MLOps Zoomcamp
In today’s fast‑paced ML landscape, deploying a model is only half the story. Continuous monitoring ensures your system stays healthy, accurate, and reliable long after go‑live. I’ve just wrapped up Module 5: Model Monitoring in the DataTalksClub MLOps Zoomcamp, and here’s what I learned—and how you can apply it to your own projects.