awesome-ml-sys-tutorial
A personal collection of ML systems learning notes, focused on RL infrastructure, inference systems, and AI infrastructure fundamentals for readers studying how these systems work.
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Overview
This repository collects the author's learning notes and blog posts on machine-learning systems, with a particular focus on reinforcement-learning infrastructure, online and offline inference systems, and AI infrastructure fundamentals. It gives readers a written path into implementation details and questions around the reliability of systems underlying research conclusions. The index includes material on topics such as omni-model inference and SGLang memory behavior, with English and Chinese versions linked for some articles. Use it as a technical study resource, not a software package.
Key features
- Learning notes on reinforcement-learning infrastructure
- Articles about online and offline inference systems
- Coverage of AI infrastructure fundamentals, including omni-model inference and SGLang memory behavior
Best for
Researchers and engineers learning about ML systems or examining how infrastructure can affect research conclusions can use these notes as a study resource.
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