awesome-production-machine-learning and awesome-mlops
These are complements that serve different purposes within MLOps: the first is a comprehensive resource library covering the full ML lifecycle (deployment, monitoring, versioning, scaling), while the second is a curated index of tools themselves, making them reference materials that users would consult together to discover and evaluate production ML solutions.
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
kelvins/awesome-mlops
:sunglasses: A curated list of awesome MLOps tools
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