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.

PraisonAI 🦞 — 雇佣一支 24/7 AI 团队。停止编写样板代码，开始交付自主且自我改进的 Agent，能够研究、规划、编码并执行任务。5 行代码即可部署，内置 memory、RAG，支持 100+ LLM。PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, RAG, and support for 100+ LLMs.

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™

IQ Series 是一个面向 Microsoft IQ 的动手学习体验：Microsoft 的企业级统一智能层，涵盖 Foundry IQ、Work IQ 和 Fabric IQ。该系列包含视频剧集、Jupyter notebook 和 Azure 部署模板。The IQ Series is a hands-on learning experience for Microsoft IQ: Microsoft's unified intelligence layer for the enterprise, spanning Foundry IQ, Work IQ, and Fabric IQ. The series includes video episodes, Jupyter notebooks, and Azure deployment templates.

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.