Getting Started with MLOps: Deploy Your First ML Model to Production

You have a working ML model in a notebook. Now what? The gap between a prototype and a production ML system is where most AI projects fail. MLOps bridges that gap. **What MLOps actually means** MLOps applies DevOps principles ? automation, versioning, monitoring ? to machine learning. The goal is to deploy models reliably, track their performance and retrain them when they drift. **The minimum viable MLOps stack** *Model versioning:* Use MLflow or Weights & Biases to track experiments, param