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密歇根大学最新AI编程课程《Applied Agentic Software Engineering》第14讲笔记发布，围绕子智能体（Subagents）展开，讲解为何需要子智能体、其工作机制、新鲜与分叉上下文的核心权衡，以及与团队、交接等概念的区别。
A curated GitHub repository lists high-quality, officially published ML course notes from top universities like MIT, Harvard, Stanford, and Caltech, replacing textbooks for serious learners.
This course note summarizes the architectural evolution from the original Transformer to modern LLMs, focusing on convergent developments such as pre-normalization, RMS normalization, and RoPE, and provides hyperparameter selection recommendations.
A user shares a GitHub repository containing detailed lecture notes for all 10 chapters of Andrew Ng's Machine Learning Specialization, written in LaTeX and automatically compiled to PDF.