privacy-preserving ML
A curated list of awesome open-source libraries for deploying, monitoring, versioning, and scaling production machine learning systems.
What is privacy-preserving ML?
Awesome Production Machine Learning is a curated, community-maintained list of open-source software libraries and tools designed for the machine learning operations (MLOps) lifecycle. It helps engineers and data scientists discover resources to deploy, monitor, version, scale, and secure their machine learning models in production environments. The project organizes tools by function, providing a comprehensive map of the production ML ecosystem.
Machine learning engineers, MLOps practitioners, data scientists, and developers who are building, deploying, and maintaining machine learning systems in production and need to navigate the vast landscape of available open-source tooling.
Developers choose this list because it saves significant research time by providing a trusted, categorized, and up-to-date directory of production-grade ML tools. It serves as a definitive starting point for building an MLOps stack, backed by an active community that ensures quality and relevance.
Overview
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Use Cases
Best For
- Discovering open-source tools for specific MLOps tasks like model serving or experiment tracking
Found a gem we're missing?
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