visenger/awesome-mlops
📦 Open Source Projectvisenger
A curated list of MLOps references, tools, and best practices for machine learning operations.
The Awesome MLOps repository is a community-driven collection of resources for Machine Learning Operations (MLOps). It includes papers, blogs, tools, frameworks, and platforms related to the end-to-end lifecycle of ML models. The list is organized into sections such as data management, model training, deployment, monitoring, and federated learning. It serves as a valuable reference for practitioners aiming to streamline ML workflows with DevOps principles.
💡Highlights
- ├─13.9k stars, 2k forks
- ├─Covers end-to-end ML lifecycle
- └─Includes federated learning resources
🎯For
- ├─ML engineers
- ├─Data scientists
- └─DevOps practitioners