This repository compiles a curated list of essential references and resources for Machine Learning Operations (MLOps).
It's an extensive "awesome list" primarily contained within its `README.md`, organized into specific MLOps domains, from core concepts and workflow management to infrastructure and ethical AI. The `README.md` provides a detailed table of contents, directing users to external articles, books, papers, and tools categorized by topics like "MLOps: Feature Stores" and "MLOps: Model Deployment and Serving".
This repository compiles a curated list of essential references and resources for Machine Learning Operations (MLOps).
Machine learning engineers, data scientists, and software developers building or managing ML systems will find this resource valuable.