仓库/Skill 库

在 PyTorch 中从零开始逐步实现一个类似 ChatGPT 的 LLM。Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

学习它，构建它，并为他人发布Learn it. Build it. Ship it for others.

O'Reilly 书籍《Hands-On Large Language Models》的官方代码仓库。Official code repo for the O'Reilly Book - "Hands-On Large Language Models"

✅（已完结）超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】

《Machine Learning for Trading》第三版配套代码——从数据获取到实盘交易全流程。Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.

机器学习工程开放手册。Machine Learning Engineering Open Book

Bartosz Milewski《Category Theory for Programmers》非官方 PDF 和 LaTeX 源码Bartosz Milewski's 'Category Theory for Programmers' unofficial PDF and LaTeX source

22 种 prompt engineering 技术，附带 Jupyter Notebook 实战教程，覆盖从基础概念到利用 LLM 的高级策略。22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.

Astrid 的权威参考：内核、capsules、host ABI、IPC 和安全模型。The canonical reference for Astrid: kernel, capsules, host ABI, IPC, and the security model.

如何参与 Astrid 开发：polyrepo 布局、内核 dumb 法则、RFC 触发机制、贡献分级与发布流程。How to work on Astrid: the polyrepo, the kernel-is-dumb law, the RFC trigger, contribution tiers, and the release process. Part of Unicity Astrid OS.

Astrid 贡献者手册：多仓库、公共契约、贡献流程和发布工作流。Contributor handbook for Astrid: the polyrepo, public contracts, contribution process, and release workflow.

美股指南

从零开始一步步用 PyTorch 实现一个推理 LLM。Implement a reasoning LLM in PyTorch from scratch, step by step

MLNLP社区用来帮助大家避免论文投稿小错误的整理仓库。 Paper Writing Tips

使用 LaTeX 撰写研究论文的技巧Tips for Writing a Research Paper using LaTeX

FDE（前沿部署工程师）从零入门指南（基于范冰《增长黑客》原书框架）

使用 LaTeX 撰写科学论文的最佳实践与技巧，图形由 Python 或 Matlab 生成Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.

帮助初学者轻松上手 LaTeX 的简明入门指南。📜 Brief Intro to LaTeX for beginners that helps you use LaTeX with ease.

Codex 橙皮书：从安装到实战案例的全链路 Codex 使用指南（非官方开源，含可下载 PDF）

《构筑大语言模型应用：应用开发与架构设计》一本关于 LLM 在真实世界应用的开源电子书，介绍了大语言模型的基础知识和应用，以及如何构建自己的模型。其中包括Prompt的编写、开发和管理，探索最好的大语言模型能带来什么，以及LLM应用开发的模式和架构设计。

www.flydean.com 的源码，AIGC,人工智能,JAVA,前端全领域覆盖,定期分享学习心得和经验,帮助大家少走弯路。觉得有帮助的话,给我点个star吧!

Anthropics/skills中文学习版本 来自：https://github.com/anthropics/skills

Best AI Humanizer Handbook——一份让 AI 辅助写作更清晰、更可信、更具人文气息的实用指南Best AI Humanizer Handbook A practical guide to making AI-assisted writing clearer, more credible, and more human

"Humanizer" 规则集，让 AI 文本更锐利、具备 genre 感知能力，包含具体锚点与 self-auditing 工作流"Humanizer" rules that make AI text sharper, genre-aware, with concrete anchors and self-auditing workflow

使用 AI 的系统文献综述（SLR）借助人工智能技术，自动加速海量学术文献的审阅与综合过程Systematic Literature Review (SLR) using AI involves leveraging artificial intelligence techniques to automate and expedite the process of reviewing and synthesizing large volumes of scholarly literature.

Obsidian.md 是一款专为学术写作打造的出色笔记应用。本仓库是"使用 AI 进行系统文献综述"研讨会活动的组成部分。Obsidian.md stands out as an exceptional note-taking application tailored specifically for academic writing. This repository is part of the activities for the Systematic Literature Review using AI workshop.

本课程涵盖从初始想法到正式学术写作的开发流程与实现要点。学生将学习如何转化与消化文献综述，从而凝练出拟定的研究题目。This course will cover the fundamental steps and implementation on developing the initial ideas to formal academic writing accordingly. Students will be given the mechanisms on how to transform and digest the literature reviews that leads to the proposed title.

走向可复现研究的初步步骤（极简教程）Initial steps toward reproducible research (a minimal tutorial)

🚀 掌握 prompt engineering，通过指南、示例与最佳实践优化 AI 交互，覆盖各技能水平与应用领域。🚀 Master prompt engineering to optimize AI interactions with guides, examples, and best practices for all skill levels and domains.

在研究全球干旱状况的同时实践可复现研究方法的项目A project to practice reproducible research practices while studying the state of drought around the world

通过真实工作流学习实践可复现研究的 R 开放教材An open educational textbook for learning reproducible research in R through practical, real-world workflows.

学习时记录的笔记素材。Materi yang dicatatkan saat belajar

教学用 LLM 应用teaching LLM applications

AI 工程路线图 2026 🚀 | 从零构建并部署 AI 应用。AI Engineering Roadmap 2026 🚀 | Build & Deploy AI Apps from Scratch