awesome-production-machine-learning and awesome-mlops
These are complementary curated reference lists that together cover overlapping but distinct aspects of ML production—the first focusing on practical open source libraries for deployment and monitoring, while the second provides a broader MLOps reference guide that likely includes both tools and conceptual frameworks.
About awesome-production-machine-learning
EthicalML/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Covers the full MLOps lifecycle across 20+ categories including feature engineering, model training orchestration, privacy-preserving techniques, and domain-specific solutions for NLP, computer vision, and recommender systems. Includes a searchable Hugging Face interface for navigating the toolchain and receives monthly updates via GitHub releases tracking newly added production-ready libraries.
About awesome-mlops
visenger/awesome-mlops
A curated list of references for MLOps
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