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Covers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning | 涵盖预训练数据、分词器、Transformer、MoE、分布式训练、缩放定律、推理与对齐，6 项渐进代码作业，掌握 LLM 全栈知识
Official SGLang x Datawhale course on LLM inference: understand inference, build a mini-sglang from scratch, then read the real SGLang source and land your first PR. Available in English and Chinese.
🌟 Datawhale 贡献者可视化平台，在线地址：https://mv.datawhale.cc/
PocketFlow from 0 to 1 ｜ 100 行代码构建所有 LLM 应用 ｜ 首个 PocketFlow 交互式教程 ｜ 光速掌握智能体开发实战
机器学习入门教程：从线性回归到神经网络，配可运行代码与图解。
🐳 AI 驱动的开源交互式学习引擎
markdown education typescript ai vue interactive-learning nestjs course-authoring datawhale llm deepseek mastery-learning
Datawhale 具身智能 Task01 学习笔记 | 从入门到实践
datawhale 李宏毅《机器学习》笔记 · Study notes from the Datawhale machine learning course based on Hung-yi Lee's lectures.
Datawhale × AMD ROCm 实战 | LoRA 微调 Gemma 4 E4B-it 完成 6 类情绪分类 | 准确率 0.625→0.915
基于 datawhalechina/all-in-rag 的学习与优化记录仓库
🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.github.io/all-in-rag/
Web version of our project.
nodejs game algorithm hackathon nextjs chatbot mongodb-atlas role-play datawhale modelscope aihackathon modelscope-studio vercelaisdk
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