Machine Learning Engineering Open Book
Practical guidance for training and operating LLM and multimodal-model systems, including infrastructure, orchestration, inference, and debugging.
Systems in Practice · Resources
My reading and reference collection, organized by purpose. Browse a topic, find a useful guide, or see what I’m reading next.
11 resources · grouped by purpose
Practical guidance for training and operating LLM and multimodal-model systems, including infrastructure, orchestration, inference, and debugging.
Debugging methods and tool-based recipes for Unix, Python, PyTorch, and compiled programs.
Examples of how users apply the Hermes agent.
Planning, Beads, and agent-swarm workflow guide.
Japanese chapter on building an environment for AI-agent development, with artifact-based trust.
Curated directory of multi-agent orchestration tools.
List of agent-orchestration frameworks and tools.
Hiring-challenge resource for AI companies.
Summary not yet added.
Also listed in [[Backend and Technical Leadership Reading List]].
Summary not yet added.
Also listed in [[Backend and Technical Leadership Reading List]].
Introduction to options trading.
No resources match these filters. Try another search or clear the filters.