What is MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that aims to reliably and efficiently deploy and maintain machine learning models in production. It bridges the gap between model development (Data Scientists) and model deployment (Operations), emphasizing automation, monitoring, and collaboration throughout the entire machine learning lifecycle. Think of it as DevOps, but specifically tailored for the unique challenges of machine learning.

Visit the following resources to learn more:

• @book@MLOps Engineering at Scale - Carl Osipov
• @article@What is MLOps?
• @article@MLOps Explained: A Deep Dive into Machine Learning Operations
• @article@Machine Learning Operations (MLOps) For Beginners
• @article@MLOps vs DevOps: Differences, Overlaps, and Use Cases
• @article@MLOps: What It Is, Why It Matters, and How to Implement It
• @video@What is MLOps?
• @video@MLOps Explained - What It Is, Why You Need It and How It Works