仓库/Skill 库

LLM 入门课程，附路线图与 Colab notebookCourse to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

开箱即用的云模板，支持 RAG、AI 流水线与企业级搜索，接入实时数据。🐳Docker 友好。⚡始终与 Sharepoint、Google Drive、S3、Kafka、PostgreSQL 以及各类实时数据 API 保持同步。Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

深入讲解 LLM、RAG 以及真实场景 AI Agent 应用的教程。In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

📚 从零开始构建大模型

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"

本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

围绕 PyTorch 在视觉、文本、强化学习等领域的一组示例。A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

50+ 教程与实现，覆盖生成式 AI Agent 技术，从基础对话机器人到复杂多 Agent 系统。50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

✅（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】

端到端、代码优先的教程，助你构建生产级 GenAI Agent，覆盖从原型到企业级部署的全流程。End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.

《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

示例 📓 Jupyter notebooks，演示如何使用 🧠 Amazon SageMaker 构建、训练和部署机器学习模型。Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Transformer 可视化解析：通过交互式可视化学习 LLM Transformer 模型的工作原理。Transformer Explained Visually: Learn How LLM Transformer Models Work with Interactive Visualization

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.

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

📚 OpenVINO™ 的 Jupyter notebook 教程。📚 Jupyter notebook tutorials for OpenVINO™

面向 agent 的纯数学工具：搜索实例与反例，进行精确计算，并独立验证结论所证内容。Pure mathematics for agents: search for examples and counterexamples, compute exactly, and independently check what a result proves.

自动更新的开源知识库，面向 AI Agent、RAG 系统、MCP server、prompt、tool、模板以及新一代 Web 开发。An auto-updating open-source vault for AI agents, RAG systems, MCP servers, prompts, tools, templates, and next-generation web development.

一个以证据为引领的六语种 LLM 实战手册：包含可迁移的核心、Codex 旗舰路线，以及 ChatGPT、Claude Code、Gemini、DeepSeek 和 Grok 的适配器。An evidence-led, six-language LLM playbook: the transferable core, the Codex flagship track, and adapters for ChatGPT, Claude Code, Gemini, DeepSeek, and Grok.

🚀 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.

微调、评估、提示工程、开源模型Fine-tuning, evaluation, prompting, open-source models

🚀 通过 70 个生成式 AI 实战项目转型技能，从入门到生产级架构师，涵盖真实场景应用。🚀 Transform your skills with 70 hands-on projects in Generative AI, guiding you from beginner to production-ready architect with real-world applications.

builderr.ai 交易 Agent 模板——fork 后实现 decide()，即可提交。Trading agent template for builderr.ai — fork this, implement decide(), submit.

教学用 LLM 应用teaching LLM applications

一个可运行的 TypeScript 教程，从零搭建一个极简 DeepSeek 风格 Agent 框架。A runnable TypeScript tutorial that builds a minimal DeepSeek-style agent harness from scratch.

使用 HTML 和 CSS 构建简洁、风格化的网站，配备响应式布局、导航与现代设计，提升用户参与度🌐 Build a simple, stylish website using HTML and CSS, featuring a responsive layout, navigation, and a modern design for easy user engagement.

GenAI 职业路线图 2026 🚀 | AI 岗位路径与技能指南GenAI Career Roadmap 2026 🚀 | AI Job Paths & Skills Guide

面向飞书/Lark 的开源 AI 辅助入职方案：可配置工作流、文档 OCR 与审阅、Bitable 同步、提醒功能，以及零凭证 Demo。Open-source AI-assisted HR onboarding for Feishu/Lark: configurable workflows, document OCR and review, Bitable sync, reminders, and a zero-credential demo.

通过实战教程构建有效的 AI 评测，使用真实 agent 提升生产系统技能🎯 Build effective AI evaluations through a hands-on tutorial, using a realistic agent to enhance your production system skills.

这是我的 ERA-V5 作业仓库。This is a repo for my assignment of ERA-V5

提供清晰的分步指南，介绍如何在 Arch Linux 上结合 rEFInd 与 Nvidia 硬件启用带模块签名强制的 Secure Boot。Provide a clear, step-by-step guide to enable Secure Boot with module signature enforcement on Arch Linux using rEFInd and Nvidia hardware.

🔧 通过灵活的 prompt 模板与任务规范项目简化 AI Agent，实现高效的指令与记忆管理。🔧 Streamline AI agents with this flexible prompt template and task specification project for effective instruction and memory management.

大语言模型（LLM）是一种人工智能（AI）程序，能够识别并生成文本，以及执行其他任务。A large language model (LLM) is a type of artificial intelligence (AI) program that can recognize and generate text, among other tasks.

本地使用 AI 总结视频，从讲座、会议和教程中提取视觉亮点与文本摘要，基于 RTX 40 系列 GPU 的 CUDA 加速Summarize videos locally with AI, extracting visual highlights and text summaries from lectures, meetings, and tutorials using CUDA on RTX 40-series GPUs