What is MLOps?

Bridging the Gap Between ML Development and Operations

Automating the Machine Learning Lifecycle

Ensuring Reliability and Scalability for AI Systems

**MLOps** (Machine Learning Operations) is a set of practices that aims to **deploy and maintain machine learning models in production reliably and efficiently**. It bridges the gap between machine learning development (data scientists) and IT operations (engineers), much like DevOps does for software development. MLOps involves automating and standardizing the entire machine learning lifecycle, from data collection and model training to deployment, monitoring, and retraining. Its goal is to ensure that AI models are robust, scalable, perform as expected in real-world environments, and can be continuously updated, making it critical for the sustained success of AI initiatives in 2025. ⚙️📊