awesome-mlops-kubernetes and awesome-ml-serving
Awesome-mlops-kubernetes is a superset of awesome-ml-serving, as Kubernetes is a common platform for deploying and scaling ML models, which includes serving them.
About awesome-mlops-kubernetes
awesome-mlops/awesome-mlops-kubernetes
A curated list of awesome open source tools and commercial products that will help you train, deploy, monitor, version, scale, and secure your production machine learning on kubernetes 🚀
Managing and operating machine learning models in a production environment can be complex. This project helps ML engineers and data scientists discover tools to streamline tasks like training, deployment, monitoring, and version control for their machine learning models. It provides a curated list of solutions that integrate with Kubernetes infrastructure.
About awesome-ml-serving
awesome-mlops/awesome-ml-serving
A curated list of awesome open source and commercial platforms for serving models in production 🚀
This list compiles tools and platforms designed to help machine learning engineers deploy their trained models so they can be used by other applications or end-users. It covers solutions for taking a developed ML model (like a recommendation engine or an image classifier) and making it accessible through an API or a user interface. This is for machine learning engineers, MLOps specialists, or data scientists responsible for moving models from development to production.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work