Let’s go step-by-step through the deployment workflow of a real-world ML REST API, following MLOps best practices. The starting point Imagine today is your first day as an ML engineer at Uber, and your task is to improve the ML service that predicts the Estimated Time of Arrival (ETA). The ETA service gives the end users an estimate of when the driver will arrive at the pickup location.