MLOps
Machine Learning Operations encompasses the practices, tools, and culture required to reliably build, deploy, and monitor ML models in production.
Think of It Like This
Like the pit crew and logistics team that keeps a high-performance Formula 1 race car running smoothly on the track.
MLOps bridges the gap between experimental data science and robust software engineering. It involves managing data pipelines, tracking experiments, automating CI/CD for models, and monitoring production deployments for concept drift. It is essential for preventing model degradation in real-world business applications.