[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-adithya-s-k--AI-Engineering.academy":3,"tool-adithya-s-k--AI-Engineering.academy":64},[4,17,27,35,43,56],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":16},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,3,"2026-04-05T11:01:52",[13,14,15],"开发框架","图像","Agent","ready",{"id":18,"name":19,"github_repo":20,"description_zh":21,"stars":22,"difficulty_score":23,"last_commit_at":24,"category_tags":25,"status":16},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",138956,2,"2026-04-05T11:33:21",[13,15,26],"语言模型",{"id":28,"name":29,"github_repo":30,"description_zh":31,"stars":32,"difficulty_score":23,"last_commit_at":33,"category_tags":34,"status":16},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",107662,"2026-04-03T11:11:01",[13,14,15],{"id":36,"name":37,"github_repo":38,"description_zh":39,"stars":40,"difficulty_score":23,"last_commit_at":41,"category_tags":42,"status":16},3704,"NextChat","ChatGPTNextWeb\u002FNextChat","NextChat 是一款轻量且极速的 AI 助手，旨在为用户提供流畅、跨平台的大模型交互体验。它完美解决了用户在多设备间切换时难以保持对话连续性，以及面对众多 AI 模型不知如何统一管理的痛点。无论是日常办公、学习辅助还是创意激发，NextChat 都能让用户随时随地通过网页、iOS、Android、Windows、MacOS 或 Linux 端无缝接入智能服务。\n\n这款工具非常适合普通用户、学生、职场人士以及需要私有化部署的企业团队使用。对于开发者而言，它也提供了便捷的自托管方案，支持一键部署到 Vercel 或 Zeabur 等平台。\n\nNextChat 的核心亮点在于其广泛的模型兼容性，原生支持 Claude、DeepSeek、GPT-4 及 Gemini Pro 等主流大模型，让用户在一个界面即可自由切换不同 AI 能力。此外，它还率先支持 MCP（Model Context Protocol）协议，增强了上下文处理能力。针对企业用户，NextChat 提供专业版解决方案，具备品牌定制、细粒度权限控制、内部知识库整合及安全审计等功能，满足公司对数据隐私和个性化管理的高标准要求。",87618,"2026-04-05T07:20:52",[13,26],{"id":44,"name":45,"github_repo":46,"description_zh":47,"stars":48,"difficulty_score":23,"last_commit_at":49,"category_tags":50,"status":16},2268,"ML-For-Beginners","microsoft\u002FML-For-Beginners","ML-For-Beginners 是由微软推出的一套系统化机器学习入门课程，旨在帮助零基础用户轻松掌握经典机器学习知识。这套课程将学习路径规划为 12 周，包含 26 节精炼课程和 52 道配套测验，内容涵盖从基础概念到实际应用的完整流程，有效解决了初学者面对庞大知识体系时无从下手、缺乏结构化指导的痛点。\n\n无论是希望转型的开发者、需要补充算法背景的研究人员，还是对人工智能充满好奇的普通爱好者，都能从中受益。课程不仅提供了清晰的理论讲解，还强调动手实践，让用户在循序渐进中建立扎实的技能基础。其独特的亮点在于强大的多语言支持，通过自动化机制提供了包括简体中文在内的 50 多种语言版本，极大地降低了全球不同背景用户的学习门槛。此外，项目采用开源协作模式，社区活跃且内容持续更新，确保学习者能获取前沿且准确的技术资讯。如果你正寻找一条清晰、友好且专业的机器学习入门之路，ML-For-Beginners 将是理想的起点。",84991,"2026-04-05T10:45:23",[14,51,52,53,15,54,26,13,55],"数据工具","视频","插件","其他","音频",{"id":57,"name":58,"github_repo":59,"description_zh":60,"stars":61,"difficulty_score":10,"last_commit_at":62,"category_tags":63,"status":16},3128,"ragflow","infiniflow\u002Fragflow","RAGFlow 是一款领先的开源检索增强生成（RAG）引擎，旨在为大语言模型构建更精准、可靠的上下文层。它巧妙地将前沿的 RAG 技术与智能体（Agent）能力相结合，不仅支持从各类文档中高效提取知识，还能让模型基于这些知识进行逻辑推理和任务执行。\n\n在大模型应用中，幻觉问题和知识滞后是常见痛点。RAGFlow 通过深度解析复杂文档结构（如表格、图表及混合排版），显著提升了信息检索的准确度，从而有效减少模型“胡编乱造”的现象，确保回答既有据可依又具备时效性。其内置的智能体机制更进一步，使系统不仅能回答问题，还能自主规划步骤解决复杂问题。\n\n这款工具特别适合开发者、企业技术团队以及 AI 研究人员使用。无论是希望快速搭建私有知识库问答系统，还是致力于探索大模型在垂直领域落地的创新者，都能从中受益。RAGFlow 提供了可视化的工作流编排界面和灵活的 API 接口，既降低了非算法背景用户的上手门槛，也满足了专业开发者对系统深度定制的需求。作为基于 Apache 2.0 协议开源的项目，它正成为连接通用大模型与行业专有知识之间的重要桥梁。",77062,"2026-04-04T04:44:48",[15,14,13,26,54],{"id":65,"github_repo":66,"name":67,"description_en":68,"description_zh":69,"ai_summary_zh":69,"readme_en":70,"readme_zh":71,"quickstart_zh":72,"use_case_zh":73,"hero_image_url":74,"owner_login":75,"owner_name":76,"owner_avatar_url":77,"owner_bio":78,"owner_company":79,"owner_location":80,"owner_email":81,"owner_twitter":82,"owner_website":83,"owner_url":84,"languages":85,"stars":109,"forks":110,"last_commit_at":111,"license":112,"difficulty_score":113,"env_os":114,"env_gpu":115,"env_ram":115,"env_deps":116,"category_tags":119,"github_topics":120,"view_count":23,"oss_zip_url":81,"oss_zip_packed_at":81,"status":16,"created_at":129,"updated_at":130,"faqs":131,"releases":142},3162,"adithya-s-k\u002FAI-Engineering.academy","AI-Engineering.academy","Mastering Applied AI, One Concept at a Time ","AI-Engineering.academy 是一个致力于让应用人工智能学习变得清晰易懂的开源教育项目。面对 AI 领域知识繁杂、入门门槛高的问题，它将核心概念拆解为循序渐进的学习路径，帮助学习者从基础理论平滑过渡到生产级实践。\n\n该项目特别适合希望系统掌握 AI 工程技能的开发者、技术研究人员以及想要提升实战能力的学生。不同于碎片化的教程，AI-Engineering.academy 提供了高度结构化的课程体系，涵盖提示词工程（Prompt Engineering）、检索增强生成（RAG）、大模型微调（Fine-tuning）、AI 智能体（Agents）构建以及模型部署等关键领域。其独特亮点在于“工业界对齐”的教学理念，不仅讲解原理，更强调通过真实世界的项目案例和端到端的代码实现，培养用户解决复杂问题的落地能力。无论是想从零构建 RAG 系统，还是优化模型部署策略，用户都能在这里找到经过验证的最佳实践与避坑指南，从而高效地成长为合格的 AI 工程师。","\u003Cdiv align=\"center\">\n  \u003Ch1> AI Engineering Academy \u003C\u002Fh1>\n  \u003Ch3>🚀 Mastering Applied AI, One Concept at a Time 🚀\u003C\u002Fh3>\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7cdcc795c24c.png\" alt=\"Ai Engineering. Academy\" width=\"60%\">\n  \u003Cp>\n    \u003Ca href=\"https:\u002F\u002Faiengineering.academy\u002F\" target=\"_blank\">Website\u003C\u002Fa> •\n    \u003Ca href=\"#roadmap\">Learning Paths\u003C\u002Fa> •\n    \u003Ca href=\"#getting-started\">Getting Started\u003C\u002Fa> •\n    \u003Ca href=\"#community\">Community\u003C\u002Fa>\n  \u003C\u002Fp>\n\u003C\u002Fdiv>\n\n[![GitHub Stars](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fstargazers)\n[![GitHub Forks](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fforks\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fnetwork\u002Fmembers)\n[![GitHub Issues](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fissues)\n[![GitHub Pull Requests](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-pr\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fpulls)\n[![License](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fblob\u002Fmain\u002FLICENSE)\n\n## 🎯 Mission\n\nYour journey into AI shouldn't be overwhelming. [AIengineering.academy](https:\u002F\u002Faiengineering.academy\u002F) curate and organize essential knowledge into clear learning paths, making complex AI concepts accessible and practical for everyone.\n\n## 🌟 Why Choose AI Engineering Academy?\n\n- 📚 **Structured Learning**: Carefully designed pathways from fundamentals to advanced concepts\n- 💻 **Hands-on Practice**: Real-world projects and implementations\n- 🎓 **Industry-Aligned**: Focus on practical, production-ready skills\n- 🤝 **Community-Driven**: Learn alongside peers and experts\n\n## 🗺️ Learning Paths\n\n### 1. [Prompt Engineering](.\u002Fdocs\u002FPromptEngineering\u002F)\n\nMaster the art of effectively communicating with AI models\n\n- Fundamental concepts and best practices\n- Advanced techniques for optimal results\n- Real-world applications and case studies\n\n### 2. [Retrieval Augmented Generation (RAG)](.\u002Fdocs\u002FRAG\u002F)\n\nEnhance AI responses with external knowledge\n\n- Core RAG architecture and components\n- Building RAG systems from scratch\n- Production deployment strategies\n- Performance optimization techniques\n\n### 3. [Fine-tuning](.\u002Fdocs\u002FLLM\u002F)\n\nCustomize AI models for your specific needs\n\n- Understanding fine-tuning fundamentals\n- Model adaptation techniques\n- Best practices and common pitfalls\n- Resource optimization\n\n### 4. [Deployment](.\u002Fdocs\u002FDeployment\u002F) 📍 _Coming Soon_\n\nTake your AI models from laptop to production\n\n- Cloud deployment strategies\n- Performance optimization\n- Scaling considerations\n- Monitoring and maintenance\n\n### 5. [AI Agents](.\u002Fdocs\u002FAgents\u002F)\n\nBuild autonomous AI systems\n\n- Agent architectures\n- Decision-making frameworks\n- Multi-agent systems\n- Real-world applications\n\n### 6. [Projects](.\u002Fdocs\u002FProjects\u002F)\n\nApply your knowledge through hands-on projects\n\n- End-to-end implementations\n- Industry-relevant scenarios\n- Portfolio-worthy demonstrations\n\n## 🚀 Getting Started\n\n1. **Choose Your Path**: Select a learning track that matches your goals\n2. **Follow the Structure**: Complete modules in the recommended order\n3. **Practice**: Implement the concepts through provided exercises\n4. **Build**: Create your own projects using the knowledge gained\n5. **Share**: Contribute to the community and help others learn\n\n## 👥 Community\n\n- Join our growing community of AI enthusiasts\n- Share your learning journey\n- Collaborate on projects\n- Get help when you're stuck\n- Contribute to improving the curriculum\n\n\u003Cdiv align=\"center\">\n  \u003Ch3>🏆 Maintainer\u003C\u002Fh3>\n  \u003Ctable>\n    \u003Ctr>\n      \u003Ctd align=\"center\">\n        \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\">\n          \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_0fca285d5686.png\" width=\"100px;\" alt=\"\"\u002F>\n          \u003Cbr \u002F>\n          \u003Csub>\u003Cb>Adithya S Kolavi\u003C\u002Fb>\u003C\u002Fsub>\n        \u003C\u002Fa>\n        \u003Cbr \u002F>\n        \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fcommits?author=adithya-s-k\" title=\"Code\">💻\u003C\u002Fa>\n      \u003C\u002Ftd>\n    \u003C\u002Ftr>\n  \u003C\u002Ftable>\n\u003C\u002Fdiv>\n\n\u003Cdiv align=\"center\">\n  \u003Ch3>Community Contributors\u003C\u002Fh3>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fgraphs\u002Fcontributors\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7f4494e9d73a.png\" \u002F>\n  \u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\u003Cp align=\"center\">\n  \u003Ch3>📈 Project Growth\u003C\u002Fh3>\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_5141bc9a3b48.png\" alt=\"Star History Chart\">\n\u003C\u002Fp>\n\n\n## 🤝 Contributing\n\nWe welcome contributions! Whether it's fixing a typo, adding new content, or suggesting improvements, every contribution helps make AI Engineering Academy better for everyone.\n\n1. Fork the repository\n2. Create your feature branch (`git checkout -b feature\u002FAmazingFeature`)\n3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)\n4. Push to the branch (`git push origin feature\u002FAmazingFeature`)\n5. Open a Pull Request\n\n## 📝 License\n\nThis project is licensed under the terms of the MIT license. See the [LICENSE](LICENSE) file for details.\n\n---\n\n\u003Cdiv align=\"center\">\n  \u003Cp>An initiative by \u003Ca href=\"https:\u002F\u002Fcognitivelab.in\u002F\" target=\"_blank\">CognitiveLab\u003C\u002Fa>\u003C\u002Fp>\n  \u003Cp>Made with ❤️ for the AI community\u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\u003C!-- \u003Cdiv align=\"center\">\n    \u003Ch1 >\u003Ca href=\"https:\u002F\u002Faiengineering.academy\u002F\" target=\"_blank\">AIEngineering.academy\u003C\u002Fa>\u003C\u002Fh1>\n    \u003Cp>Navigating the World of AI, One Step at a Time\u003C\u002Fp>\n    \u003Cp>Initiative from \u003Ca href=\"https:\u002F\u002Fcognitivelab.in\u002F\" target=\"_blank\">CognitiveLab\u003C\u002Fa>\u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7cdcc795c24c.png\" alt=\"Ai Engineering. Academy\">\n\n\n[![GitHub Stars](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fstargazers)\n[![GitHub Forks](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fforks\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fnetwork\u002Fmembers)\n[![GitHub Issues](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fissues)\n[![GitHub Pull Requests](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-pr\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fpulls)\n[![License](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fblob\u002Fmain\u002FLICENSE)\n\n\n\nAI-related careers are becoming increasingly sought-after. However, the abundance of learning resources scattered across the internet can lead to confusion about where to start. \n\n**AI Engineering Academy** aims to provide a structured learning path to help you learn Applied GenAI effectively.\n\n## Roadmap\n\n### [**1. Prompt Engineering**](PromptEngineering\u002F)\n\nThis roadmap will cover the basics of prompt engineering and its role in various AI applications.\n\n### [**2. Retrieval Augmented Generation (RAG)**](RAG\u002F)\n\nIf you've been in the AI space, you might have heard of RAG (Retrieval Augmented Generation). In this roadmap, we will cover:\n\n- Understanding what RAG is\n- Implementing RAG from scratch without using any frameworks\n- Choosing the best RAG system for your needs\n- Taking a RAG system to production\n\n### [**3. Fine-tuning**](Finetuning\u002F)\n\n**(coming soon)**\n\nWe will debunk some myths about fine-tuning and explore where it can be effectively used. Fine-tuning can be a powerful tool, but it's often misunderstood. Expect to learn:\n\n- The true potential of fine-tuning\n- Proper techniques for fine-tuning models\n\n### [**4. Deployment**](Deployment\u002F)\n\n**(coming soon)**\n\nWhile everything might work perfectly locally, putting models into the hands of users requires careful consideration. In this roadmap, we will cover:\n\n- Deploying ML and DL models into production\n- Working with different cloud providers\n- Exploring various deployment modes\n\n### [**5. AI Agents**](Agents\u002F)\n\n**(coming soon)**\n\n### [**6. Projects**](Projects\u002F)\n\n**(coming soon)**\n\nConsists of multiple hands-on end-to-end AI projects!!\n\n## Repo Admin 👨‍💼\n\n\u003Cdiv align=\"center\">\n  \u003Ctable>\n    \u003Ctr>\n      \u003Ctd align=\"center\">\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\">\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_0fca285d5686.png\" width=\"100px;\" alt=\"\"\u002F>\u003Cbr \u002F>\u003Csub>\u003Cb>Adithya S Kolavi\u003C\u002Fb>\u003C\u002Fsub>\u003C\u002Fa>\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fcommits?author=adithya-s-k\" title=\"Code\">💻\u003C\u002Fa>\u003C\u002Ftd>\n    \u003C\u002Ftr>\n  \u003C\u002Ftable>\n\u003C\u002Fdiv>\n\n## Contributors 🌟\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fgraphs\u002Fcontributors\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7f4494e9d73a.png\" \u002F>\n\nThanks to these wonderful people for their contributions!\n\u003C\u002Fa>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fadithyask.com\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_5141bc9a3b48.png\" alt=\"Star History Chart\">\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003C!-- \u003Cdiv align=\"center\">\n    \u003Ch1 >\u003Ca href=\"https:\u002F\u002Faiengineering.academy\u002F\" target=\"_blank\">AIEngineering.academy\u003C\u002Fa>\u003C\u002Fh1>\n    \u003Cp>Navigating the World of AI, One Step at a Time\u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7cdcc795c24c.png\" alt=\"Ai Engineering. Academy\">\n\n\u003Cdiv align=\"center\">\n\n[![GitHub Stars](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fstargazers)\n[![GitHub Forks](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fforks\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fnetwork\u002Fmembers)\n[![GitHub Issues](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fissues)\n[![GitHub Pull Requests](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-pr\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fpulls)\n[![License](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fblob\u002Fmain\u002FLICENSE)\n\n\u003C\u002Fdiv>\n\nAI-related careers are becoming increasingly sought-after. However, the abundance of learning resources scattered across the internet can lead to confusion about where to start. \n\n**AI Engineering Academy** aims to provide a structured learning path to help you learn Applied GenAI effectively.\n\n## Roadmaps\n\n**AIEngineering.academy** offers multiple structured roadmaps to learn different domains in Applied GenAI.\n\n### [**Retrieval Augmented Generation (RAG)**](RAG\u002F)\n\nIf you've been in the AI space, you might have heard of RAG (Retrieval Augmented Generation). In this roadmap, we will cover:\n\n- Understanding what RAG is\n- Implementing RAG from scratch without using any frameworks\n- Choosing the best RAG system for your needs\n- Taking a RAG system to production\n\n### [**Fine-tuning**](Finetuning\u002F)\n\n**(coming soon)**\n\nWe will debunk some myths about fine-tuning and explore where it can be effectively used. Fine-tuning can be a powerful tool, but it's often misunderstood. Expect to learn:\n\n- The true potential of fine-tuning\n- Proper techniques for fine-tuning models\n\n### [**Deployment**](Deployment\u002F)\n\n**(coming soon)**\n\nWhile everything might work perfectly locally, putting models into the hands of users requires careful consideration. In this roadmap, we will cover:\n\n- Deploying ML and DL models into production\n- Working with different cloud providers\n- Exploring various deployment modes\n\nEach roadmap is designed to provide a comprehensive learning experience, equipping you with the knowledge and skills to excel in applied GenAI.\n\n### [AI Agents](Agents\u002F)\n\n**(coming soon)**\n\n### [Projects](Projects\u002F)\n\n**(coming soon)**\n\nConsists on multiple Hands of End to End AI projects !!\n\n## Applied AI RoadMap\n\n## Repo Admin 👨‍💼\n\n\u003Cdiv align=\"center\">\n  \u003Ctable>\n    \u003Ctr>\n      \u003Ctd align=\"center\">\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\">\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_0fca285d5686.png\" width=\"100px;\" alt=\"\"\u002F>\u003Cbr \u002F>\u003Csub>\u003Cb>Adithya S Kolavi\u003C\u002Fb>\u003C\u002Fsub>\u003C\u002Fa>\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FCognitiveLab-tech\u002FWorld-of-AI\u002Fcommits?author=adithya-s-k\" title=\"Code\">💻\u003C\u002Fa>\u003C\u002Ftd>\n    \u003C\u002Ftr>\n  \u003C\u002Ftable>\n\u003C\u002Fdiv>\n\n## Contributors 🌟\n\nThanks to these wonderful people for their contributions!\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FCognitiveLab-tech\u002FWorld-of-AI\u002Fgraphs\u002Fcontributors\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_9c0cd61dcd95.png\" \u002F>\n\u003C\u002Fa>\n\nIf you liked working on this project, do ⭐ and share this repository.\n\n© 2023 CognitiveLab\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fadithyask.com\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_5141bc9a3b48.png\" alt=\"Star History Chart\">\n  \u003C\u002Fa>\n\u003C\u002Fp> -->\n","\u003Cdiv align=\"center\">\n  \u003Ch1> AI 工程学院 \u003C\u002Fh1>\n  \u003Ch3>🚀 每次掌握一个应用型 AI 概念 🚀\u003C\u002Fh3>\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7cdcc795c24c.png\" alt=\"Ai Engineering. Academy\" width=\"60%\">\n  \u003Cp>\n    \u003Ca href=\"https:\u002F\u002Faiengineering.academy\u002F\" target=\"_blank\">官网\u003C\u002Fa> •\n    \u003Ca href=\"#roadmap\">学习路径\u003C\u002Fa> •\n    \u003Ca href=\"#getting-started\">开始学习\u003C\u002Fa> •\n    \u003Ca href=\"#community\">社区\u003C\u002Fa>\n  \u003C\u002Fp>\n\u003C\u002Fdiv>\n\n[![GitHub 星标](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fstargazers)\n[![GitHub 分支](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fforks\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fnetwork\u002Fmembers)\n[![GitHub 问题](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fissues)\n[![GitHub 拉取请求](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-pr\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fpulls)\n[![许可证](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fblob\u002Fmain\u002FLICENSE)\n\n## 🎯 使命\n\n踏入 AI 领域的旅程不必令人望而生畏。[AIengineering.academy](https:\u002F\u002Faiengineering.academy\u002F) 将关键知识精心整理并划分为清晰的学习路径，让复杂的 AI 概念对每个人来说都既易于理解又实用。\n\n## 🌟 为什么选择 AI 工程学院？\n\n- 📚 **结构化学习**：从基础到高级概念的精心设计路径\n- 💻 **实践导向**：真实世界的项目与实现\n- 🎓 **行业接轨**：专注于实用且可投入生产的技能\n- 🤝 **社区驱动**：与同行和专家共同学习\n\n## 🗺️ 学习路径\n\n### 1. [提示工程](.\u002Fdocs\u002FPromptEngineering\u002F)\n\n掌握与 AI 模型有效沟通的艺术\n\n- 基础概念与最佳实践\n- 实现最优效果的进阶技巧\n- 现实应用场景与案例分析\n\n### 2. [检索增强生成（RAG）](.\u002Fdocs\u002FRAG\u002F)\n\n利用外部知识增强 AI 的响应能力\n\n- RAG 的核心架构与组件\n- 从零构建 RAG 系统\n- 生产环境部署策略\n- 性能优化技术\n\n### 3. [微调](.\u002Fdocs\u002FLLM\u002F)\n\n根据您的特定需求定制 AI 模型\n\n- 微调的基础知识\n- 模型适配技术\n- 最佳实践与常见陷阱\n- 资源优化\n\n### 4. [部署](.\u002Fdocs\u002FDeployment\u002F) 📍 _即将推出_\n\n将您的 AI 模型从笔记本电脑带到生产环境\n\n- 云端部署策略\n- 性能优化\n- 扩展性考量\n- 监控与维护\n\n### 5. [AI 代理](.\u002Fdocs\u002FAgents\u002F)\n\n构建自主 AI 系统\n\n- 代理架构\n- 决策框架\n- 多智能体系统\n- 实际应用\n\n### 6. [项目](.\u002Fdocs\u002FProjects\u002F)\n\n通过动手项目应用所学知识\n\n- 端到端实现\n- 行业相关场景\n- 可用于作品集的演示\n\n## 🚀 开始学习\n\n1. **选择你的路径**：根据你的目标选择合适的学习方向\n2. **按照结构学习**：按推荐顺序完成各个模块\n3. **实践**：通过提供的练习来实现这些概念\n4. **构建**：利用所学知识创建自己的项目\n5. **分享**：为社区贡献力量，帮助他人学习\n\n## 👥 社区\n\n- 加入我们不断壮大的 AI 爱好者社区\n- 分享你的学习历程\n- 共同参与项目\n- 在遇到困难时获得帮助\n- 为改进课程体系贡献力量\n\n\u003Cdiv align=\"center\">\n  \u003Ch3>🏆 维护者\u003C\u002Fh3>\n  \u003Ctable>\n    \u003Ctr>\n      \u003Ctd align=\"center\">\n        \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\">\n          \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_0fca285d5686.png\" width=\"100px;\" alt=\"\"\u002F>\n          \u003Cbr \u002F>\n          \u003Csub>\u003Cb>Adithya S Kolavi\u003C\u002Fb>\u003C\u002Fsub>\n        \u003C\u002Fa>\n        \u003Cbr \u002F>\n        \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fcommits?author=adithya-s-k\" title=\"代码\">💻\u003C\u002Fa>\n      \u003C\u002Ftd>\n    \u003C\u002Ftr>\n  \u003C\u002Ftable>\n\u003C\u002Fdiv>\n\n\u003Cdiv align=\"center\">\n  \u003Ch3>社区贡献者\u003C\u002Fh3>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fgraphs\u002Fcontributors\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7f4494e9d73a.png\" \u002F>\n  \u003C\u002Fa>\n\u003C\u002Fdiv>\n\n\u003Cp align=\"center\">\n  \u003Ch3>📈 项目增长\u003C\u002Fh3>\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_5141bc9a3b48.png\" alt=\"星标历史图\">\n\u003C\u002Fp>\n\n\n## 🤝 贡献\n\n我们欢迎任何形式的贡献！无论是修正拼写错误、添加新内容，还是提出改进建议，每一份贡献都能让 AI 工程学院变得更好，惠及更多人。\n\n1. 分支仓库\n2. 创建功能分支 (`git checkout -b feature\u002FAmazingFeature`)\n3. 提交更改 (`git commit -m 'Add some AmazingFeature'`)\n4. 推送到分支 (`git push origin feature\u002FAmazingFeature`)\n5. 打开拉取请求\n\n## 📝 许可证\n\n本项目采用 MIT 许可证授权。详情请参阅 [LICENSE](LICENSE) 文件。\n\n---\n\n\u003Cdiv align=\"center\">\n  \u003Cp>由 \u003Ca href=\"https:\u002F\u002Fcognitivelab.in\u002F\" target=\"_blank\">CognitiveLab\u003C\u002Fa> 发起\u003C\u002Fp>\n  \u003Cp>用心为 AI 社区打造\u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\u003C!-- \u003Cdiv align=\"center\">\n    \u003Ch1 >\u003Ca href=\"https:\u002F\u002Faiengineering.academy\u002F\" target=\"_blank\">AIEngineering.academy\u003C\u002Fa>\u003C\u002Fh1>\n    \u003Cp>一步步探索 AI 的世界\u003C\u002Fp>\n    \u003Cp>由 \u003Ca href=\"https:\u002F\u002Fcognitivelab.in\u002F\" target=\"_blank\">CognitiveLab\u003C\u002Fa> 发起\u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7cdcc795c24c.png\" alt=\"Ai Engineering. Academy\">\n\n\n[![GitHub 星标](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fstargazers)\n[![GitHub 分支](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fforks\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fnetwork\u002Fmembers)\n[![GitHub 问题](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fissues)\n[![GitHub 拉取请求](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-pr\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fpulls)\n[![许可证](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fblob\u002Fmain\u002FLICENSE)\n\n\n\n与 AI 相关的职业正变得越来越受欢迎。然而，互联网上充斥着大量的学习资源，这可能会让人感到不知从何入手。 \n\n**AI 工程学院**旨在提供一条结构化的学习路径，帮助您高效地学习应用型通用 AI。\n\n## 路线图\n\n### [**1. 提示工程**](PromptEngineering\u002F)\n\n本路线图将涵盖提示工程的基础知识及其在各类AI应用中的作用。\n\n### [**2. 检索增强生成（RAG）**](RAG\u002F)\n\n如果你涉足过AI领域，或许已经听说过RAG（Retrieval Augmented Generation）。在本路线图中，我们将探讨：\n\n- 理解什么是RAG\n- 从零开始实现RAG，不使用任何框架\n- 如何为你的需求选择最佳的RAG系统\n- 将RAG系统部署到生产环境\n\n### [**3. 微调**](Finetuning\u002F)\n\n**(即将推出)**\n\n我们将揭穿关于微调的一些误解，并探索其可以有效应用的场景。微调是一项强大的工具，但常常被误解。你将了解到：\n\n- 微调的真正潜力\n- 正确的模型微调技巧\n\n### [**4. 部署**](Deployment\u002F)\n\n**(即将推出)**\n\n尽管在本地环境中一切可能运行得完美无缺，但要将模型交付给用户使用，则需要仔细考量。在本路线图中，我们将介绍：\n\n- 将机器学习和深度学习模型部署到生产环境\n- 与不同云服务提供商合作\n- 探索多种部署模式\n\n### [**5. AI智能体**](Agents\u002F)\n\n**(即将推出)**\n\n### [**6. 项目**](Projects\u002F)\n\n**(即将推出)**\n\n包含多个实战性的端到端AI项目！！\n\n## 仓库管理员 👨‍💼\n\n\u003Cdiv align=\"center\">\n  \u003Ctable>\n    \u003Ctr>\n      \u003Ctd align=\"center\">\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\">\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_0fca285d5686.png\" width=\"100px;\" alt=\"\"\u002F>\u003Cbr \u002F>\u003Csub>\u003Cb>Adithya S Kolavi\u003C\u002Fb>\u003C\u002Fsub>\u003C\u002Fa>\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fcommits?author=adithya-s-k\" title=\"代码\">💻\u003C\u002Fa>\u003C\u002Ftd>\n    \u003C\u002Ftr>\n  \u003C\u002Ftable>\n\u003C\u002Fdiv>\n\n## 贡献者 🌟\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fgraphs\u002Fcontributors\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7f4494e9d73a.png\" \u002F>\n\n感谢这些优秀的人士所做的贡献！\n\u003C\u002Fa>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fadithyask.com\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_5141bc9a3b48.png\" alt=\"星数变化图\">\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003C!-- \u003Cdiv align=\"center\">\n    \u003Ch1 >\u003Ca href=\"https:\u002F\u002Faiengineering.academy\u002F\" target=\"_blank\">AIEngineering.academy\u003C\u002Fa>\u003C\u002Fh1>\n    \u003Cp>循序渐进，探索AI世界\u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_7cdcc795c24c.png\" alt=\"Ai Engineering. Academy\">\n\n\u003Cdiv align=\"center\">\n\n[![GitHub Star](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fstargazers)\n[![GitHub Fork](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fforks\u002Fadithya-s-k\u002FAI-Engineering.academy?style=social)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fnetwork\u002Fmembers)\n[![GitHub Issues](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fissues)\n[![GitHub Pull Requests](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-pr\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fpulls)\n[![License](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fadithya-s-k\u002FAI-Engineering.academy)](https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fblob\u002Fmain\u002FLICENSE)\n\n\u003C\u002Fdiv>\n\n与AI相关的职业正变得越来越受欢迎。然而，互联网上充斥着大量的学习资源，这往往让人不知从何入手。  \n\n**AI Engineering Academy** 致力于提供一条结构化的学习路径，帮助你高效地学习应用型通用AI。\n\n## 路线图\n\n**AIEngineering.academy** 提供多条结构化的路线图，用于学习应用型通用AI的不同领域。\n\n### [**检索增强生成（RAG）**](RAG\u002F)\n\n如果你涉足过AI领域，或许已经听说过RAG（Retrieval Augmented Generation）。在本路线图中，我们将探讨：\n\n- 理解什么是RAG\n- 从零开始实现RAG，不使用任何框架\n- 如何为你的需求选择最佳的RAG系统\n- 将RAG系统部署到生产环境\n\n### [**微调**](Finetuning\u002F)\n\n**(即将推出)**\n\n我们将揭穿关于微调的一些误解，并探索其可以有效应用的场景。微调是一项强大的工具，但常常被误解。你将了解到：\n\n- 微调的真正潜力\n- 正确的模型微调技巧\n\n### [**部署**](Deployment\u002F)\n\n**(即将推出)**\n\n尽管在本地环境中一切可能运行得完美无缺，但要将模型交付给用户使用，则需要仔细考量。在本路线图中，我们将介绍：\n\n- 将机器学习和深度学习模型部署到生产环境\n- 与不同云服务提供商合作\n- 探索多种部署模式\n\n每条路线图都旨在提供全面的学习体验，使你掌握在应用型通用AI领域取得成功所需的知识和技能。\n\n### [AI智能体](Agents\u002F)\n\n**(即将推出)**\n\n### [项目](Projects\u002F)\n\n**(即将推出)**\n\n包含多个端到端的AI实战项目！！ \n\n## 应用AI路线图\n\n## 仓库管理员 👨‍💼\n\n\u003Cdiv align=\"center\">\n  \u003Ctable>\n    \u003Ctr>\n      \u003Ctd align=\"center\">\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fadithya-s-k\">\u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_0fca285d5686.png\" width=\"100px;\" alt=\"\"\u002F>\u003Cbr \u002F>\u003Csub>\u003Cb>Adithya S Kolavi\u003C\u002Fb>\u003C\u002Fsub>\u003C\u002Fa>\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FCognitiveLab-tech\u002FWorld-of-AI\u002Fcommits?author=adithya-s-k\" title=\"代码\">💻\u003C\u002Fa>\u003C\u002Ftd>\n    \u003C\u002Ftr>\n  \u003C\u002Ftable>\n\u003C\u002Fdiv>\n\n## 贡献者 🌟\n\n感谢这些优秀的人士所做的贡献！\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FCognitiveLab-tech\u002FWorld-of-AI\u002Fgraphs\u002Fcontributors\">\n  \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_9c0cd61dcd95.png\" \u002F>\n\u003C\u002Fa>\n\n如果你喜欢这个项目，请为它点亮星星并分享这个仓库。\n\n© 2023 CognitiveLab\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fadithyask.com\">\n    \u003Cimg src=\"https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_readme_5141bc9a3b48.png\" alt=\"星数变化图\">\n  \u003C\u002Fa>\n\u003C\u002Fp> -->","# AI Engineering Academy 快速上手指南\n\nAI Engineering Academy 不是一个需要安装的软件包或框架，而是一个**结构化的开源学习知识库**。它提供了从提示词工程到 RAG、微调及 Agent 开发的完整学习路径和实战代码。\n\n以下是开始学习的步骤：\n\n## 1. 环境准备\n\n由于本仓库包含多个领域的实战项目（如 RAG、Fine-tuning），建议根据你的学习路径准备相应的 Python 环境。\n\n*   **操作系统**: Windows, macOS, 或 Linux\n*   **Python 版本**: 推荐 `Python 3.9` 或更高版本\n*   **前置依赖**:\n    *   Git (用于克隆仓库)\n    *   pip 或 conda (用于管理依赖)\n    *   基础深度学习库 (根据具体章节需求安装，如 `torch`, `transformers`, `langchain` 等)\n\n> 💡 **国内加速建议**:\n> 建议使用国内镜像源安装 Python 依赖，以提升下载速度：\n> ```bash\n> pip install -r requirements.txt -i https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple\n> ```\n\n## 2. 安装步骤 (获取学习内容)\n\n通过 Git 克隆仓库到本地，即可获取所有教程文档和示例代码。\n\n```bash\n# 克隆仓库\ngit clone https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy.git\n\n# 进入项目目录\ncd AI-Engineering.academy\n```\n\n*注：不同学习路径（如 RAG 或 Agents）目录下通常会有独立的 `requirements.txt`，请在进入对应目录后按需安装。*\n\n## 3. 基本使用 (开始学习)\n\n本项目没有统一的启动命令，使用方式是**选择一条学习路径**，阅读文档并运行对应的示例代码。\n\n### 步骤 A: 选择学习路径\n进入你感兴趣的领域目录，例如学习 **RAG (检索增强生成)**：\n\n```bash\ncd docs\u002FRAG\u002F\n```\n\n其他可用路径包括：\n*   `docs\u002FPromptEngineering\u002F` - 提示词工程\n*   `docs\u002FLLM\u002F` - 模型微调 (Fine-tuning)\n*   `docs\u002FAgents\u002F` - AI Agent 开发\n*   `docs\u002FProjects\u002F` - 端到端实战项目\n\n### 步骤 B: 安装该路径依赖\n在当前路径下安装特定教程所需的库：\n\n```bash\n# 假设该目录下有 requirements.txt\npip install -r requirements.txt -i https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple\n```\n\n### 步骤 C: 运行示例代码\n按照目录中的 Markdown 文档说明，运行具体的 Python 脚本。例如，在 RAG 目录中可能会看到类似以下的示例：\n\n```bash\n# 示例：运行一个从头构建的 RAG 系统\npython rag_from_scratch.py\n```\n\n### 步骤 D: 在线访问 (可选)\n如果你只想阅读文档而不克隆代码，可以直接访问官方网站：\n👉 [https:\u002F\u002Faiengineering.academy\u002F](https:\u002F\u002Faiengineering.academy\u002F)\n\n---\n\n**下一步建议**:\n完成基础模块后，前往 `docs\u002FProjects\u002F` 目录，尝试构建完整的端到端项目以巩固技能，并欢迎向仓库提交 Pull Request 贡献你的代码。","某初创公司的后端工程师李明，需要在两周内为内部知识库构建一个能准确回答公司文档的智能问答系统。\n\n### 没有 AI-Engineering.academy 时\n- **学习路径混乱**：面对 RAG、微调、Prompt 工程等海量概念，不知从何入手，花费大量时间在碎片化博客和过时教程中摸索。\n- **理论脱离实战**：虽然看懂了算法原理，但缺乏从数据清洗到向量数据库搭建的完整代码示例，导致项目迟迟无法启动。\n- **生产落地困难**：自行编写的原型在本地运行尚可，一旦考虑部署上线，便对性能优化、延迟控制和监控维护毫无头绪。\n- **试错成本高昂**：因不了解常见陷阱（如幻觉问题或上下文窗口限制），反复修改架构，严重拖慢了交付进度。\n\n### 使用 AI-Engineering.academy 后\n- **路线清晰高效**：直接跟随平台提供的\"RAG 学习路径”，按部就班地从核心架构学到生产部署策略，迅速建立起系统性认知。\n- **手把手实战指引**：利用提供的端到端项目案例，快速复现了一个基于公司文档的 RAG 系统，将原本需要数周的调研压缩至几天。\n- **具备工程化思维**：通过学习\"Deployment\"和\"Fine-tuning\"模块，掌握了模型量化、云端部署及监控维护的关键技巧，确保系统稳定运行。\n- **规避常见坑点**：参考最佳实践指南，提前解决了数据切分粒度不当和检索精度低等典型问题，一次性通过内部测试。\n\nAI-Engineering.academy 将零散的 AI 知识转化为结构化的工程能力，帮助开发者从“纸上谈兵”快速进阶为能交付生产级应用的实战专家。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fadithya-s-k_AI-Engineering.academy_7cdcc795.png","adithya-s-k","Adithya S K","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002Fadithya-s-k_40ebffb1.jpg","Shipping @huggingface  ","huggingface","Indian",null,"adithya_s_k","https:\u002F\u002Fadithyask.com\u002F","https:\u002F\u002Fgithub.com\u002Fadithya-s-k",[86,90,94,98,102,106],{"name":87,"color":88,"percentage":89},"Jupyter Notebook","#DA5B0B",97.6,{"name":91,"color":92,"percentage":93},"Python","#3572A5",1.9,{"name":95,"color":96,"percentage":97},"JavaScript","#f1e05a",0.3,{"name":99,"color":100,"percentage":101},"Shell","#89e051",0.1,{"name":103,"color":104,"percentage":105},"CSS","#663399",0,{"name":107,"color":108,"percentage":105},"HTML","#e34c26",2168,252,"2026-04-03T16:38:05","MIT",1,"","未说明",{"notes":117,"python":115,"dependencies":118},"该项目主要是一个结构化的学习指南和文档集合（包含提示工程、RAG、微调等路径），而非一个可直接运行的单一软件包。README 中未列出具体的运行环境、依赖库或硬件需求。具体的环境要求将取决于用户在跟随教程进行“动手实践”时选择实现的具体项目或模型。",[],[13,26],[121,122,123,124,125,126,127,128],"fine-tuning","finetuning","finetuning-llms","inference","large-language-models","llm","python","quantization","2026-03-27T02:49:30.150509","2026-04-06T07:13:06.353748",[132,137],{"id":133,"question_zh":134,"answer_zh":135,"source_url":136},14558,"为什么在开始训练前要设置 `tokenizer.pad_token = tokenizer.eos_token`？","将填充令牌（pad token）设置为句子结束令牌（EOS token）是因为数据集中的数据长度不一。在微调过程中，如果上下文窗口为 8k tokens，而分词后的数据只有 7k tokens，剩余空间会用 EOS token 填充。这样可以确保在推理阶段，模型在应该结束回复时生成 EOS token，而不是重复生成或产生无关内容。虽然某些模型有专用的 PAD token，但在微调时，将 pad token 设为 EOS 是避免重复生成的良好实践。","https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fissues\u002F2",{"id":138,"question_zh":139,"answer_zh":140,"source_url":141},14559,"这个项目有 JavaScript 版本的仓库吗？","目前该仓库的主要关注点是 Python。不过，欢迎社区贡献者共同参与开发 JavaScript 版本。","https:\u002F\u002Fgithub.com\u002Fadithya-s-k\u002FAI-Engineering.academy\u002Fissues\u002F10",[]]