MLOps Explained - What It Is, Why You Need It and How It Works

A comprehensive introduction to MLOps covering the challenges of deploying ML models to production, illustrated with a banking fraud detection example. Explains how MLOps bridges the gap between data science and DevOps, covering the complete lifecycle from data collection to production deployment. Ideal for Data Scientists, DevOps Engineers, and Cloud Engineers looking to operationalize ML models.