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Lanxiang Hu 2025-03-17 00:05:10 +00:00
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docs/机器学习系统/MLSYS.en.md
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@ -14,7 +14,7 @@ The curriculum is divided into three main sections:
1. **Fundamentals**: Covers topics such as deep learning, automatic differentiation, and an overview of machine learning systems. 1. **Fundamentals**: Covers topics such as deep learning, automatic differentiation, and an overview of machine learning systems.
2. **Machine Learning Systems and Optimization**: Includes subjects like dataflow graph systems, machine learning compilation, memory and graph optimizations, and distributed machine learning optimization. 2. **Machine Learning Systems and Optimization**: Includes subjects like machine learning compilation, memory and graph optimizations, and distributed machine learning optimization.
3. **Large (Language) Models**: Explores cutting-edge topics such as training of large language models (LLMs), data preparation, inference and serving, attention mechanism optimization, and retrieval-augmented generation (RAG). 3. **Large (Language) Models**: Explores cutting-edge topics such as training of large language models (LLMs), data preparation, inference and serving, attention mechanism optimization, and retrieval-augmented generation (RAG).

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docs/机器学习系统/MLSYS.md
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@ -22,7 +22,7 @@
1. 基础知识：​包括深度学习、自动微分、机器学习系统概述等。 1. 基础知识：​包括深度学习、自动微分、机器学习系统概述等。
2. 机器学习系统与优化：​涵盖数据流图系统、机器学习编译、内存与图优化、分布式机器学习优化等主题。 2. 机器学习系统与优化：机器学习编译、内存与图优化、分布式机器学习优化等主题。
3. 大（语言）模型：​探讨LLM的训练、数据准备、推理与服务、注意力机制优化、检索增强生成（RAG）等前沿话题。​ 3. 大（语言）模型：​探讨LLM的训练、数据准备、推理与服务、注意力机制优化、检索增强生成（RAG）等前沿话题。​