Awesome MLOps

A curated list of awesome open source libraries to deploy, monitor, version, and scale machine learning systems in production. Focuses on MLOps, model serving, and production-ready ML tools.

A curated list of open source and commercial feature store tools and platforms for machine learning, including Feast, Hopsworks, and Tecton, enabling consistent feature management across training and serving for production ML systems.

Curated resources for deploying, monitoring, versioning, and scaling machine learning models in production environments, combining DevOps practices with ML engineering (ML + DevOps = MLOps).

A curated collection of tools, frameworks, platforms, and best practices for operationalizing Large Language Models, covering deployment, monitoring, evaluation, and production workflows.

Study notes and a curated list of awesome resources for Artificial Intelligence, Machine Learning and Deep Learning including frameworks, tutorials, research papers, and educational materials.

A comprehensive curated list covering all machine learning topics including learning paradigms, tasks, applications, models, ethics, cross-disciplinary areas, datasets, frameworks, and tutorials.