[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-ashishpatel26--500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code":3,"tool-ashishpatel26--500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code":61},[4,18,26,36,44,53],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":17},4358,"openclaw","openclaw\u002Fopenclaw","OpenClaw 是一款专为个人打造的本地化 AI 助手，旨在让你在自己的设备上拥有完全可控的智能伙伴。它打破了传统 AI 助手局限于特定网页或应用的束缚，能够直接接入你日常使用的各类通讯渠道，包括微信、WhatsApp、Telegram、Discord、iMessage 等数十种平台。无论你在哪个聊天软件中发送消息，OpenClaw 都能即时响应，甚至支持在 macOS、iOS 和 Android 设备上进行语音交互，并提供实时的画布渲染功能供你操控。\n\n这款工具主要解决了用户对数据隐私、响应速度以及“始终在线”体验的需求。通过将 AI 部署在本地，用户无需依赖云端服务即可享受快速、私密的智能辅助，真正实现了“你的数据，你做主”。其独特的技术亮点在于强大的网关架构，将控制平面与核心助手分离，确保跨平台通信的流畅性与扩展性。\n\nOpenClaw 非常适合希望构建个性化工作流的技术爱好者、开发者，以及注重隐私保护且不愿被单一生态绑定的普通用户。只要具备基础的终端操作能力（支持 macOS、Linux 及 Windows WSL2），即可通过简单的命令行引导完成部署。如果你渴望拥有一个懂你",349277,3,"2026-04-06T06:32:30",[13,14,15,16],"Agent","开发框架","图像","数据工具","ready",{"id":19,"name":20,"github_repo":21,"description_zh":22,"stars":23,"difficulty_score":10,"last_commit_at":24,"category_tags":25,"status":17},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,"2026-04-05T11:01:52",[14,15,13],{"id":27,"name":28,"github_repo":29,"description_zh":30,"stars":31,"difficulty_score":32,"last_commit_at":33,"category_tags":34,"status":17},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",154349,2,"2026-04-13T23:32:16",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":32,"last_commit_at":42,"category_tags":43,"status":17},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。",108322,"2026-04-10T11:39:34",[14,15,13],{"id":45,"name":46,"github_repo":47,"description_zh":48,"stars":49,"difficulty_score":32,"last_commit_at":50,"category_tags":51,"status":17},6121,"gemini-cli","google-gemini\u002Fgemini-cli","gemini-cli 是一款由谷歌推出的开源 AI 命令行工具，它将强大的 Gemini 大模型能力直接集成到用户的终端环境中。对于习惯在命令行工作的开发者而言，它提供了一条从输入提示词到获取模型响应的最短路径，无需切换窗口即可享受智能辅助。\n\n这款工具主要解决了开发过程中频繁上下文切换的痛点，让用户能在熟悉的终端界面内直接完成代码理解、生成、调试以及自动化运维任务。无论是查询大型代码库、根据草图生成应用，还是执行复杂的 Git 操作，gemini-cli 都能通过自然语言指令高效处理。\n\n它特别适合广大软件工程师、DevOps 人员及技术研究人员使用。其核心亮点包括支持高达 100 万 token 的超长上下文窗口，具备出色的逻辑推理能力；内置 Google 搜索、文件操作及 Shell 命令执行等实用工具；更独特的是，它支持 MCP（模型上下文协议），允许用户灵活扩展自定义集成，连接如图像生成等外部能力。此外，个人谷歌账号即可享受免费的额度支持，且项目基于 Apache 2.0 协议完全开源，是提升终端工作效率的理想助手。",100752,"2026-04-10T01:20:03",[52,13,15,14],"插件",{"id":54,"name":55,"github_repo":56,"description_zh":57,"stars":58,"difficulty_score":32,"last_commit_at":59,"category_tags":60,"status":17},4721,"markitdown","microsoft\u002Fmarkitdown","MarkItDown 是一款由微软 AutoGen 团队打造的轻量级 Python 工具，专为将各类文件高效转换为 Markdown 格式而设计。它支持 PDF、Word、Excel、PPT、图片（含 OCR）、音频（含语音转录）、HTML 乃至 YouTube 链接等多种格式的解析，能够精准提取文档中的标题、列表、表格和链接等关键结构信息。\n\n在人工智能应用日益普及的今天，大语言模型（LLM）虽擅长处理文本，却难以直接读取复杂的二进制办公文档。MarkItDown 恰好解决了这一痛点，它将非结构化或半结构化的文件转化为模型“原生理解”且 Token 效率极高的 Markdown 格式，成为连接本地文件与 AI 分析 pipeline 的理想桥梁。此外，它还提供了 MCP（模型上下文协议）服务器，可无缝集成到 Claude Desktop 等 LLM 应用中。\n\n这款工具特别适合开发者、数据科学家及 AI 研究人员使用，尤其是那些需要构建文档检索增强生成（RAG）系统、进行批量文本分析或希望让 AI 助手直接“阅读”本地文件的用户。虽然生成的内容也具备一定可读性，但其核心优势在于为机器",93400,"2026-04-06T19:52:38",[52,14],{"id":62,"github_repo":63,"name":64,"description_en":65,"description_zh":66,"ai_summary_zh":67,"readme_en":68,"readme_zh":69,"quickstart_zh":70,"use_case_zh":71,"hero_image_url":72,"owner_login":73,"owner_name":74,"owner_avatar_url":75,"owner_bio":76,"owner_company":77,"owner_location":78,"owner_email":79,"owner_twitter":80,"owner_website":81,"owner_url":82,"languages":80,"stars":83,"forks":84,"last_commit_at":85,"license":80,"difficulty_score":86,"env_os":87,"env_gpu":88,"env_ram":88,"env_deps":89,"category_tags":92,"github_topics":94,"view_count":32,"oss_zip_url":80,"oss_zip_packed_at":80,"status":17,"created_at":108,"updated_at":109,"faqs":110,"releases":111},7385,"ashishpatel26\u002F500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code","500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code","500 AI Machine learning Deep learning Computer vision NLP Projects with code","500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code 是一个汇聚了超过 500 个人工智能实战项目的开源资源库。它全面覆盖了机器学习、深度学习、计算机视觉和自然语言处理（NLP）等核心领域，为每个项目提供了完整的代码实现与详细解析。\n\n对于许多希望进入 AI 领域的学习者和开发者而言，最大的痛点往往不是缺乏理论，而是缺少能够直接上手、逻辑清晰的实战案例。这个资源库正是为了解决这一“从理论到实践”的鸿沟而生。它不仅整理了如时间序列预测、情感分析、推荐系统、聊天机器人构建等具体应用场景的代码，还包含了吴恩达（Andrew NG）的机器学习笔记等经典学习资料，帮助用户在复现代码的过程中深入理解算法原理。\n\n该项目非常适合 AI 初学者、计算机专业学生、软件开发者以及数据科学研究人员使用。无论是想要丰富个人作品集的求职者，还是寻求灵感的技术专家，都能从中找到适合的练习题材。其独特的亮点在于内容的持续更新与广泛性：从基础的 Python GUI 开发到前沿的 Transformer 模型应用，所有","500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code 是一个汇聚了超过 500 个人工智能实战项目的开源资源库。它全面覆盖了机器学习、深度学习、计算机视觉和自然语言处理（NLP）等核心领域，为每个项目提供了完整的代码实现与详细解析。\n\n对于许多希望进入 AI 领域的学习者和开发者而言，最大的痛点往往不是缺乏理论，而是缺少能够直接上手、逻辑清晰的实战案例。这个资源库正是为了解决这一“从理论到实践”的鸿沟而生。它不仅整理了如时间序列预测、情感分析、推荐系统、聊天机器人构建等具体应用场景的代码，还包含了吴恩达（Andrew NG）的机器学习笔记等经典学习资料，帮助用户在复现代码的过程中深入理解算法原理。\n\n该项目非常适合 AI 初学者、计算机专业学生、软件开发者以及数据科学研究人员使用。无论是想要丰富个人作品集的求职者，还是寻求灵感的技术专家，都能从中找到适合的练习题材。其独特的亮点在于内容的持续更新与广泛性：从基础的 Python GUI 开发到前沿的 Transformer 模型应用，所有链接均经过测试确保可用，且欢迎社区贡献。通过将庞大的知识体系拆解为一个个可执行的小项目，它让复杂的 AI 技术变得触手可及，是提升编程技能与算法理解的优质指南。","## 500 + 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗟𝗶𝘀𝘁 𝘄𝗶𝘁𝗵 𝗰𝗼𝗱𝗲\r\n\r\n***500 AI Machine learning Deep learning Computer vision NLP Projects with code* !!!**\r\n\r\n![](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fashishpatel26_500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code_readme_04deb5d4fedd.gif)\r\n\r\nFollow me on LinkedIn : [![](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white)](https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fashishpatel2604\u002F)\r\n\r\n***This list is continuously updated.*** - You can take pull requests and contribute. All Links are tested and working fine. Please ping if any link doesn't work\r\n\r\n| Sr No | Name                                                         | Link                                                         |\r\n| ----- | ------------------------------------------------------------ | ------------------------------------------------------------ |\r\n| 1     | 365 Days Computer Vision Learning                            | [👆](https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002F365-Days-Computer-Vision-Learning-Linkedin-Post) |\r\n| 2     | 125+ NLP Language Models Treasure of Transformers            | [👆](https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002FTreasure-of-Transformers) |\r\n| 3     | Andrew NG ML notes                                           | [👆](https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002FAndrew-NG-Notes)        |\r\n| 4     | 10 Machine Learning Projects on Time Series Forecasting      | [👆](https:\u002F\u002Fmedium.com\u002Fcoders-camp\u002F10-machine-learning-projects-on-time-seri%20es-forecasting-ee0368420ccd) |\r\n| 5     | 20 Deep Learning Projects Solved and Explained with Python   | [👆](https:\u002F\u002Fthecleverprogrammer.com\u002F2020\u002F11\u002F22\u002Fdeep-learning-projects-with-python\u002F) |\r\n| 6     | 20 Machine learning Project                                  | [👆](https:\u002F\u002Famankharwal.medium.com\u002F20-machine-learning-projects-for-portfolio-81e3dbd167b1) |\r\n| 7     | 30 Python Project Solved and Explained                       | [👆](https:\u002F\u002Famankharwal.medium.com\u002F30-python-projects-solved-and-explained-563fd7473003) |\r\n| 8     | Machine learning Course for Free                             | [👆](https:\u002F\u002Fthecleverprogrammer.com\u002F2020\u002F09\u002F24\u002Fmachine-learning-course\u002F) |\r\n| 9     | 5 Web Scraping Projects with Python                          | [👆](https:\u002F\u002Famankharwal.medium.com\u002F5-web-scraping-projects-with-python-4bcc25ff039) |\r\n| 10    | 20 Machine Learning Projects on Future Prediction with Python | [👆](https:\u002F\u002Famankharwal.medium.com\u002F20-machine-learning-projects-on-future-prediction-with-python-93932d9a7f7f) |\r\n| 11    | 4 Chatbot Project With Python                                | [👆](https:\u002F\u002Famankharwal.medium.com\u002F4-chatbot-projects-with-python-5b32fd84af37) |\r\n| 12    | 7 Python Gui project                                         | [👆](https:\u002F\u002Famankharwal.medium.com\u002F7-python-gui-projects-for-beginners-87ae2c695d78) |\r\n| 13    | All Unsupervised learning Projects                           | [👆](https:\u002F\u002Famankharwal.medium.com\u002Fall-unsupervised-machine-learning-algorithms-explained-aecf1ba95d8b) |\r\n| 14    | 10 Machine learning Projects for Regression Analysis         | [👆](https:\u002F\u002Famankharwal.medium.com\u002F10-machine-learning-projects-on-regression-with-python-e5494615a0d0) |\r\n| 15    | 10 Machine learning Project for Classification with Python   | [👆](https:\u002F\u002Fmedium.datadriveninvestor.com\u002F10-machine-learning-projects-on-classification-with-python-9261add2e8a7) |\r\n| 16    | 6 Sentimental Analysis Projects with python                  | [👆](https:\u002F\u002Famankharwal.medium.com\u002F6-sentiment-analysis-projects-with-python-1fdd3d43d90f) |\r\n| 17    | 4 Recommendations Projects with Python                       | [👆](https:\u002F\u002Fmedium.com\u002Fcoders-camp\u002F4-recommendation-system-projects-with-python-5934de32ba7d) |\r\n| 18    | 20 Deep learning Project with python                         | [👆](https:\u002F\u002Fmedium.com\u002Fcoders-camp\u002F20-deep-learning-projects-with-python-3c56f7e6a721) |\r\n| 19    | 5 COVID19 Projects with Python                               | [👆](https:\u002F\u002Famankharwal.medium.com\u002F5-covid-19-projects-with-python-and-machine-learning-63d51cde96e2) |\r\n| 20    | 9 Computer Vision Project with python                        | [👆](https:\u002F\u002Fbecominghuman.ai\u002Fcomputer-vision-projects-with-python-ecfac58ded18) |\r\n| 21    | 8 Neural Network Project with python                         | [👆](https:\u002F\u002Fmedium.datadriveninvestor.com\u002F8-neural-networks-projects-solved-and-explained-a4f142bc10c) |\r\n| 22    | 5 Machine learning Project for healthcare                    | [👆](https:\u002F\u002Fmedium.datadriveninvestor.com\u002F5-machine-learning-projects-for-healthcare-bbd0eac57b4a) |\r\n| 23    | 5 NLP Project with Python                                    | [👆](https:\u002F\u002Fmedium.datadriveninvestor.com\u002F5-nlp-projects-for-machine-learning-72d3234381d4) |\r\n| 24    | 47 Machine Learning Projects for 2021                        | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fmachine-learning-project-ideas\u002F) |\r\n| 25    | 19 Artificial Intelligence Projects for 2021                 | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fartificial-intelligence-project-ideas\u002F) |\r\n| 26    | 28 Machine learning Projects for 2021                        | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fmachine-learning-project-ideas\u002F) |\r\n| 27    | 16 Data Science Projects with Source Code for 2021           | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fdata-science-project-ideas\u002F) |\r\n| 28    | 23 Deep learning Projects with Source Code for 2021          | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fdeep-learning-project-ideas\u002F) |\r\n| 29    | 25 Computer Vision Projects with Source Code for 2021        | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fcomputer-vision-project-ideas\u002F) |\r\n| 30    | 23 Iot Projects with Source Code for 2021                    | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fiot-project-ideas\u002F)    |\r\n| 31    | 27 Django Projects with Source Code for 2021                 | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fdjango-project-ideas\u002F) |\r\n| 32    | 37 Python Fun Projects with Code for 2021                    | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fpython-project-ideas\u002F) |\r\n| 33    | 500 + Top Deep learning Codes                                | [👆](https:\u002F\u002Fgithub.com\u002Faymericdamien\u002FTopDeepLearning)        |\r\n| 34    | 500 + Machine learning Codes                                 | [👆](https:\u002F\u002Fgithub.com\u002Fjosephmisiti\u002Fawesome-machine-learning) |\r\n| 35    | 20+ Machine Learning Datasets & Project Ideas                | [👆](https:\u002F\u002Fwww.kdnuggets.com\u002F2020\u002F03\u002F20-machine-learning-datasets-project-ideas.html) |\r\n| 36    | 1000+ Computer vision codes                                  | [👆](https:\u002F\u002Fgithub.com\u002Fjbhuang0604\u002Fawesome-computer-vision)  |\r\n| 37    | 300 + Industry wise Real world projects with code            | [👆](https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002FReal-time-ML-Project)   |\r\n| 38    | 1000 + Python Project Codes                                  | [👆](https:\u002F\u002Fgithub.com\u002Fvinta\u002Fawesome-python)                 |\r\n| 39    | 363 + NLP Project with Code                                  | [👆](https:\u002F\u002Fgithub.com\u002Ffighting41love\u002FfunNLP)                |\r\n| 40    | 50 + Code ML Models (For iOS 11) Projects                    | [👆](https:\u002F\u002Fgithub.com\u002Flikedan\u002FAwesome-CoreML-Models)        |\r\n| 41    | 360+ Pretrained Model Projects for Image, text, Audio and Video | [👆](https:\u002F\u002Fgithub.com\u002FPaddlePaddle\u002FPaddleHub)               |\r\n| 42    | 50 + Graph Classification Project List                       | [👆](https:\u002F\u002Fgithub.com\u002Fbenedekrozemberczki\u002Fawesome-graph-classification) |\r\n| 43    | 100 + Sentence Embedding(NLP Resources)                      | [👆](https:\u002F\u002Fgithub.com\u002FSeparius\u002Fawesome-sentence-embedding)  |\r\n| 44    | 100 + Production Machine learning Projects                   | [👆](https:\u002F\u002Fgithub.com\u002FEthicalML\u002Fawesome-production-machine-learning) |\r\n| 45    | 300 + Machine Learning Resources Collection                  | [👆](https:\u002F\u002Fgithub.com\u002Fujjwalkarn\u002FMachine-Learning-Tutorials) |\r\n| 46    | 70 + Awesome AI                                              | [👆](https:\u002F\u002Fgithub.com\u002FNirantK\u002Fawesome-project-ideas)        |\r\n| 47    | 150 + Machine learning Project Ideas with code               | [👆](https:\u002F\u002Fgithub.com\u002Fsrc-d\u002Fawesome-machine-learning-on-source-code) |\r\n| 48    | 100 + AutoML Projects with code                              | [👆](https:\u002F\u002Fgithub.com\u002Fhibayesian\u002Fawesome-automl-papers)     |\r\n| 49    | 100 + Machine Learning Model Interpretability Code Frameworks | [👆](https:\u002F\u002Fgithub.com\u002Fjphall663\u002Fawesome-machine-learning-interpretability) |\r\n| 50    | 120 + Multi Model Machine learning Code Projects             | [👆](https:\u002F\u002Fgithub.com\u002Fpliang279\u002Fawesome-multimodal-ml)      |\r\n| 51    | Awesome Chatbot Projects                                     | [👆](https:\u002F\u002Fgithub.com\u002Ffendouai\u002FAwesome-Chatbot)             |\r\n| 52    | Awesome ML Demo Project with iOS                             | [👆](https:\u002F\u002Fgithub.com\u002Ftucan9389\u002Fawesome-ml-demos-with-ios)  |\r\n| 53    | 100 + Python based Machine learning Application Projects     | [👆](https:\u002F\u002Fgithub.com\u002Fprateekiiest\u002FCode-Sleep-Python)       |\r\n| 54    | 100 + Reproducible Research Projects of ML and DL            | [👆](https:\u002F\u002Fgithub.com\u002Fleipzig\u002Fawesome-reproducible-research) |\r\n| 55    | 25 + Python Projects                                         | [👆](https:\u002F\u002Fgithub.com\u002Fsaadhaxxan\u002FAwesome-Python-Projects)   |\r\n| 56    | 8 + OpenCV Projects                                          | [👆](https:\u002F\u002Fgithub.com\u002Fmoadmmh\u002FAwesome-OpenCV)               |\r\n| 57    | 1000 + Awesome Deep learning Collection                      | [👆](https:\u002F\u002Fgithub.com\u002FChristosChristofidis\u002Fawesome-deep-learning) |\r\n| 58    | 200 + Awesome NLP learning Collection                        | [👆](https:\u002F\u002Fgithub.com\u002Fkeon\u002Fawesome-nlp)                     |\r\n| 59    | 200 + The Super Duper NLP Repo                               | [👆](https:\u002F\u002Fnotebooks.quantumstat.com\u002F)                      |\r\n| 60    | 100 + NLP dataset for your Projects                          | [👆](https:\u002F\u002Findex.quantumstat.com\u002F#dataset)                  |\r\n| 61    | 364 + Machine Learning Projects definition                   | [👆](https:\u002F\u002Fprojectworlds.in\u002Ffree-projects\u002Fmachine-learning-projects-with-source-code\u002F) |\r\n| 62    | 300+ Google Earth Engine Jupyter Notebooks to Analyze Geospatial Data | [👆](https:\u002F\u002Fgithub.com\u002Fgiswqs\u002Fearthengine-py-notebooks)      |\r\n| 63    | 1000 + Machine learning Projects Information                 | [👆](https:\u002F\u002F1000projects.org\u002Fprojects\u002Fmachine-learning-projects) |\r\n| 64.   | 11 Computer Vision Projects with code                        | [👆](https:\u002F\u002Fgithub.com\u002Fakshaybhatia10\u002FComputerVision-Projects) |\r\n| 65.   | 13 Computer Vision Projects with Code                        | [👆](https:\u002F\u002Fgithub.com\u002Fanuragreddygv323\u002Fcomputer-vision-projects) |\r\n| 66.   | 13 Cool Computer Vision GitHub Projects To Inspire You       | [👆](https:\u002F\u002Fmachinelearningknowledge.ai\u002Fcool-computer-vision-github-projects-to-inspire-you\u002F) |\r\n| 67.   | Open-Source Computer Vision Projects (With Tutorials)        | [👆](https:\u002F\u002Fwww.theclickreader.com\u002Fopen-source-computer-vision-projects-with-tutorials\u002F) |\r\n| 68.   | OpenCV Computer Vision Projects with Python                  | [👆](https:\u002F\u002Fgithub.com\u002FPacktPublishing\u002FOpenCV-Computer-Vision-Projects-with-Python) |\r\n| 69.   | 100 + Computer vision Algorithm Implementation               | [👆](https:\u002F\u002Fgithub.com\u002Fgmalivenko\u002Fawesome-computer-vision-models) |\r\n| 70.   | 80 + Computer vision Learning code                           | [👆](https:\u002F\u002Fgithub.com\u002Fspmallick\u002Flearnopencv)                |\r\n| 71.   | Deep learning Treasure                                       | [👆](https:\u002F\u002Fgithub.com\u002Fkmario23\u002Fdeep-learning-drizzle)       |\r\n| 72    | Data Analysis and Machine learning Projects                  | [👆](https:\u002F\u002Fgithub.com\u002Frhiever\u002FData-Analysis-and-Machine-Learning-Projects) |\r\n| 73    | AI Projects                                                  | [👆](https:\u002F\u002Fgithub.com\u002FStevenLei2017\u002FAI_projects)            |\r\n| 74    | Kaggle projects collection                                   | [👆](https:\u002F\u002Fgithub.com\u002Falexattia\u002FData-Science-Projects)      |\r\n| 75    | Unique AI projects                                           | [👆](https:\u002F\u002Fgithub.com\u002Frobsalgado\u002Fpersonal_data_science_projects) |\r\n| 76    | Data Science Project Collection                              | [👆](https:\u002F\u002Fgithub.com\u002Ftuangauss\u002FDataScienceProjects)        |\r\n| 77    | Advance Data Science Projects                                | [👆](https:\u002F\u002Fgithub.com\u002FTheCodex-Me\u002FProjects)                 |\r\n| 78    | Deep and Machine learning Projects                           | [👆](https:\u002F\u002Fgithub.com\u002Fnitinkaushik01\u002FDeep_and_Machine_Learning_Projects) |\r\n| 79    | Data Science Projects kaggle                                 | [👆](https:\u002F\u002Fgithub.com\u002Falexattia\u002FData-Science-Projects)      |\r\n| 80    | Auto Deep learning Project                                   | [👆](https:\u002F\u002Fgithub.com\u002FD-X-Y\u002FAutoDL-Projects)                |\r\n| 81    | 180 Machine learning Project                                 | [👆](https:\u002F\u002Fmedium.com\u002Fcoders-camp\u002F180-data-science-and-machine-learning-projects-with-python-6191bc7b9db9) |\r\n| 82    | Amazing Hackthon Project Collection                          | [👆](https:\u002F\u002Fgithub.com\u002Fanalyticsindiamagazine\u002FMachineHack\u002Ftree\u002Fmaster\u002FHackathon_Solutions) |\r\n| 83    | Awesome NLP Project Ideas                                    | [👆](https:\u002F\u002Fnirantk.com\u002Fawesome-project-ideas\u002F)              |\r\n| 84    | 12 NLP Projects                                              | [👆](https:\u002F\u002Fgithub.com\u002Fgaoisbest\u002FNLP-Projects)               |\r\n| 85    | Advance NLP Projects                                         | [👆](https:\u002F\u002Fgithub.com\u002FPacktPublishing\u002FAdvanced-NLP-Projects-with-TensorFlow-2.0) |\r\n| 86    | 6 Amazing NLP Projects                                       | [👆](https:\u002F\u002Fgithub.com\u002Fanujvyas\u002FNatural-Language-Processing-Projects) |\r\n| 87    | NLP Beginner Projects                                        | [👆](https:\u002F\u002Fgithub.com\u002Fpositivepeng\u002Fnlp-beginner-projects)   |\r\n| 88    | Paper with Code by PwC Collection                            | [👆](https:\u002F\u002Fgithub.com\u002Fzziz\u002Fpwc)                             |\r\n| 89    | SOTA Models(State of the Art Results)                        | [👆](https:\u002F\u002Fgithub.com\u002FRedditSota\u002Fstate-of-the-art-result-for-machine-learning-problems) |\r\n| 90    | Best AI Papers                                               | [👆](https:\u002F\u002Fgithub.com\u002Flouisfb01\u002FBest_AI_paper_2020)         |\r\n| 91    | Generative Adversarial nets                                  | [👆](https:\u002F\u002Fgithub.com\u002Fzhangqianhui\u002FAdversarialNetsPapers)   |\r\n| 92    | Computer Vision Paper with Code                              | [👆](https:\u002F\u002Fgithub.com\u002FDWCTOD\u002FCVPR2022-Papers-with-Code-Demo) |\r\n| 93    | NILMS Paper with code                                        | [👆](https:\u002F\u002Fgithub.com\u002Fklemenjak\u002Fnilm-papers-with-code)      |\r\n| 94    | 3D Computer Vision Research Projects                         | [👆](https:\u002F\u002Fgithub.com\u002FTom-Hardy-3D-Vision-Workshop\u002Fawesome-3D-vision) |\r\n| 95    | NLP and Computer Vision Project Collection                   | [👆](https:\u002F\u002Fgithub.com\u002FNELSONZHAO\u002Fzhihu)                     |\r\n| 96    | Udacity Collection of Computer Vision Projects               | [👆](https:\u002F\u002Fgithub.com\u002FBjarten\u002Fcomputer-vision-ND)           |\r\n| 97    | Zero to Hero Tensorflow Tutorial                             | [👆](https:\u002F\u002Fgithub.com\u002Fmrdbourke\u002Ftensorflow-deep-learning)   |\r\n| 98    | Deep learning in Production                                  | [👆](https:\u002F\u002Fgithub.com\u002FThe-AI-Summer\u002FDeep-Learning-In-Production) |\r\n| 99    | GANs Collection                                              | [👆](https:\u002F\u002Fgithub.com\u002FThe-AI-Summer\u002FGANs-in-Computer-Vision) |\r\n| 100   | Time Series Projects Code                                    | [👆](https:\u002F\u002Fgithub.com\u002Fdeshpandenu\u002FTime-Series-Forecasting-of-Amazon-Stock-Prices-using-Neural-Networks-LSTM-and-GAN-) |\r\n| 101   | 12 Machine learning Object Detection                         | [👆](https:\u002F\u002Famankharwal.medium.com\u002F12-machine-learning-projects-on-object-detection-46b32adc3c37) |\r\n| 102   | 20 NLP Project with Python                                   | [👆](https:\u002F\u002Fmedium.com\u002Fcoders-camp\u002F20-machine-learning-projects-on-nlp-582effe73b9c) |\r\n| 103   | Learning Material for Deep Learning, ML, Computer Vision and NLP   | [👆](https:\u002F\u002Fgithub.com\u002Fkmario23\u002Fdeep-learning-drizzle) |\r\n***More Projects list is coming...!!!***\r\n\r\n---\r\n\r\n","## 500+ 个人工智能项目列表（附代码）\n\n***500个AI、机器学习、深度学习、计算机视觉、NLP项目，附带代码* !!!**\n\n![](https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fashishpatel26_500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code_readme_04deb5d4fedd.gif)\n\n在LinkedIn上关注我：[![](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white)](https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fashishpatel2604\u002F)\n\n***本列表持续更新中。*** 欢迎提交Pull Request并参与贡献。所有链接均已测试，运行正常。如发现失效链接，请及时告知。\n\n| 序号 | 名称                                                         | 链接                                                         |\n| ----- | ------------------------------------------------------------ | ------------------------------------------------------------ |\n| 1     | 365天计算机视觉学习                            | [👆](https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002F365-Days-Computer-Vision-Learning-Linkedin-Post) |\n| 2     | 125+ NLP语言模型——Transformer宝库            | [👆](https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002FTreasure-of-Transformers) |\n| 3     | 吴恩达机器学习笔记                                           | [👆](https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002FAndrew-NG-Notes)        |\n| 4     | 10个基于时间序列预测的机器学习项目      | [👆](https:\u002F\u002Fmedium.com\u002Fcoders-camp\u002F10-machine-learning-projects-on-time-seri%20es-forecasting-ee0368420ccd) |\n| 5     | 20个用Python解决并讲解的深度学习项目   | [👆](https:\u002F\u002Fthecleverprogrammer.com\u002F2020\u002F11\u002F22\u002Fdeep-learning-projects-with-python\u002F) |\n| 6     | 20个机器学习项目                                  | [👆](https:\u002F\u002Famankharwal.medium.com\u002F20-machine-learning-projects-for-portfolio-81e3dbd167b1) |\n| 7     | 30个用Python解决并讲解的项目                       | [👆](https:\u002F\u002Famankharwal.medium.com\u002F30-python-projects-solved-and-explained-563fd7473003) |\n| 8     | 免费机器学习课程                             | [👆](https:\u002F\u002Fthecleverprogrammer.com\u002F2020\u002F09\u002F24\u002Fmachine-learning-course\u002F) |\n| 9     | 5个用Python实现的网页爬取项目                          | [👆](https:\u002F\u002Famankharwal.medium.com\u002F5-web-scraping-projects-with-python-4bcc25ff039) |\n| 10    | 20个用Python进行未来预测的机器学习项目 | [👆](https:\u002F\u002Famankharwal.medium.com\u002F20-machine-learning-projects-on-future-prediction-with-python-93932d9a7f7f) |\n| 11    | 4个用Python实现的聊天机器人项目                                | [👆](https:\u002F\u002Famankharwal.medium.com\u002F4-chatbot-projects-with-python-5b32fd84af37) |\n| 12    | 7个Python GUI项目                                         | [👆](https:\u002F\u002Famankharwal.medium.com\u002F7-python-gui-projects-for-beginners-87ae2c695d78) |\n| 13    | 所有无监督学习项目                           | [👆](https:\u002F\u002Famankharwal.medium.com\u002Fall-unsupervised-machine-learning-algorithms-explained-aecf1ba95d8b) |\n| 14    | 10个用于回归分析的机器学习项目         | [👆](https:\u002F\u002Famankharwal.medium.com\u002F10-machine-learning-projects-on-regression-with-python-e5494615a0d0) |\n| 15    | 10个用Python实现的分类机器学习项目   | [👆](https:\u002F\u002Fmedium.datadriveninvestor.com\u002F10-machine-learning-projects-on-classification-with-python-9261add2e8a7) |\n| 16    | 6个用Python实现的情感分析项目                  | [👆](https:\u002F\u002Famankharwal.medium.com\u002F6-sentiment-analysis-projects-with-python-1fdd3d43d90f) |\n| 17    | 4个用Python实现的推荐系统项目                       | [👆](https:\u002F\u002Fmedium.coder-camp\u002F4-recommendation-system-projects-with-python-5934de32ba7d) |\n| 18    | 20个用Python实现的深度学习项目                         | [👆](https:\u002F\u002Fmedium.coder-camp\u002F20-deep-learning-projects-with-python-3c56f7e6a721) |\n| 19    | 5个用Python和机器学习实现的COVID-19项目               | [👆](https:\u002F\u002Famankharwal.medium.com\u002F5-covid-19-projects-with-python-and-machine-learning-63d51cde96e2) |\n| 20    | 9个用Python实现的计算机视觉项目                        | [👆](https:\u002F\u002Fbecominghuman.ai\u002Fcomputer-vision-projects-with-python-ecfac58ded18) |\n| 21    | 8个用Python实现的神经网络项目                         | [👆](https:\u002F\u002Fmedium.datadriveninvestor.com\u002F8-neural-networks-projects-solved-and-explained-a4f142bc10c) |\n| 22    | 5个用于医疗健康的机器学习项目                    | [👆](https:\u002F\u002Fmedium.datadriveninvestor.com\u002F5-machine-learning-projects-for-healthcare-bbd0eac57b4a) |\n| 23    | 5个用Python实现的NLP项目                                    | [👆](https:\u002F\u002Fmedium.datadriveninvestor.com\u002F5-nlp-projects-for-machine-learning-72d3234381d4) |\n| 24    | 47个2021年的机器学习项目                                   | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fmachine-learning-project-ideas\u002F) |\n| 25    | 19个2021年人工智能项目                                      | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fartificial-intelligence-project-ideas\u002F) |\n| 26    | 28个2021年机器学习项目                                     | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fmachine-learning-project-ideas\u002F) |\n| 27    | 16个带有源代码的数据科学项目，适用于2021年           | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fdata-science-project-ideas\u002F) |\n| 28    | 23个带有源代码的2021年深度学习项目                      | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fdeep-learning-project-ideas\u002F) |\n| 29    | 25个带有源代码的2021年计算机视觉项目                   | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fcomputer-vision-project-ideas\u002F) |\n| 30    | 23个带有源代码的2021年物联网项目                        | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fiot-project-ideas\u002F)    |\n| 31    | 27个带有源代码的2021年Django项目                         | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fdjango-project-ideas\u002F) |\n| 32    | 37个有趣的Python项目，附带代码，适用于2021年             | [👆](https:\u002F\u002Fdata-flair.training\u002Fblogs\u002Fpython-project-ideas\u002F) |\n| 33    | 500多个顶级深度学习代码                                 | [👆](https:\u002F\u002Fgithub.com\u002Faymericdamien\u002FTopDeepLearning)        |\n| 34    | 500多个机器学习代码                                     | [👆](https:\u002F\u002Fgithub.com\u002Fjosephmisiti\u002Fawesome-machine-learning) |\n| 35    | 20多个机器学习数据集及项目创意                         | [👆](https:\u002F\u002Fwww.kdnuggets.com\u002F2020\u002F03\u002F20-machine-learning-datasets-project-ideas.html) |\n| 36    | 1000多个计算机视觉代码                                  | [👆](https:\u002F\u002Fgithub.com\u002Fjbhuang0604\u002Fawesome-computer-vision)  |\n| 37    | 300多个行业实际应用项目，附带代码                      | [👆](https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002FReal-time-ML-Project)   |\n| 38    | 1000多个Python项目代码                                  | [👆](https:\u002F\u002Fgithub.com\u002Fvinta\u002Fawesome-python)                 |\n| 39    | 363多个带有代码的NLP项目                                 | [👆](https:\u002F\u002Fgithub.com\u002Ffighting41love\u002FfunNLP)                |\n| 40    | 50多个用于iOS 11的ML模型代码项目                        | [👆](https:\u002F\u002Fgithub.com\u002Flikedan\u002FAwesome-CoreML-Models)        |\n| 41    | 360多个针对图像、文本、音频和视频的预训练模型项目 | [👆](https:\u002F\u002Fgithub.com\u002FPaddlePaddle\u002FPaddleHub)               |\n| 42    | 50多个图分类项目列表                                     | [👆](https:\u002F\u002Fgithub.com\u002Fbenedekrozemberczki\u002Fawesome-graph-classification) |\n| 43    | 100多个句子嵌入（NLP资源）                               | [👆](https:\u002F\u002Fgithub.com\u002FSeparius\u002Fawesome-sentence-embedding)  |\n| 44    | 100多个生产环境中的机器学习项目                         | [👆](https:\u002F\u002Fgithub.com\u002FEthicalML\u002Fawesome-production-machine-learning) |\n| 45    | 300多个机器学习资源合集                                 | [👆](https:\u002F\u002Fgithub.com\u002Fujjwalkarn\u002FMachine-Learning-Tutorials) |\n| 46    | 70多个优秀的人工智能项目                                | [👆](https:\u002F\u002Fgithub.com\u002FNirantK\u002Fawesome-project-ideas)        |\n| 47    | 150多个带有代码的机器学习项目创意                       | [👆](https:\u002F\u002Fgithub.com\u002Fsrc-d\u002Fawesome-machine-learning-on-source-code) |\n| 48    | 100多个带有代码的AutoML项目                              | [👆](https:\u002F\u002Fgithub.com\u002Fhibayesian\u002Fawesome-automl-papers)     |\n| 49    | 100多个机器学习模型可解释性代码框架                     | [👆](https:\u002F\u002Fgithub.com\u002Fjphall663\u002Fawesome-machine-learning-interpretability) |\n| 50    | 120多个多模态机器学习代码项目                           | [👆](https:\u002F\u002Fgithub.com\u002Fpliang279\u002Fawesome-multimodal-ml)      |\n| 51    | 优秀的聊天机器人项目                                     | [👆](https:\u002F\u002Fgithub.com\u002Ffendouai\u002FAwesome-Chatbot)             |\n| 52    | 优秀的iOS机器学习演示项目                                | [👆](https:\u002F\u002Fgithub.com\u002Ftucan9389\u002Fawesome-ml-demos-with-ios)  |\n| 53    | 100多个基于Python的机器学习应用项目                     | [👆](https:\u002F\u002Fgithub.com\u002Fprateekiiest\u002FCode-Sleep-Python)       |\n| 54    | 100多个可重复研究的ML和DL项目                           | [👆](https:\u002F\u002Fgithub.com\u002Fleipzig\u002Fawesome-reproducible-research) |\n| 55    | 25多个Python项目                                          | [👆](https:\u002F\u002Fgithub.com\u002Fsaadhaxxan\u002FAwesome-Python-Projects)   |\n| 56    | 8个OpenCV项目                                             | [👆](https:\u002F\u002Fgithub.com\u002Fmoadmmh\u002FAwesome-OpenCV)               |\n| 57    | 1000多个优秀的深度学习合集                              | [👆](https:\u002F\u002Fgithub.com\u002FChristosChristofidis\u002Fawesome-deep-learning) |\n| 58    | 200多个优秀的NLP学习合集                                 | [👆](https:\u002F\u002Fgithub.com\u002Fkeon\u002Fawesome-nlp)                     |\n| 59    | 200多个超级强大的NLP仓库                                 | [👆](https:\u002F\u002Fnotebooks.quantumstat.com\u002F)                      |\n| 60    | 100多个可用于项目的NLP数据集                            | [👆](https:\u002F\u002Findex.quantumstat.com\u002F#dataset)                  |\n| 61    | 364多个机器学习项目定义                                   | [👆](https:\u002F\u002Fprojectworlds.in\u002Ffree-projects\u002Fmachine-learning-projects-with-source-code\u002F) |\n| 62    | 300多个Google Earth Engine Jupyter笔记本，用于分析地理空间数据 | [👆](https:\u002F\u002Fgithub.com\u002Fgiswqs\u002Fearthengine-py-notebooks)      |\n| 63    | 1000多个机器学习项目信息                                 | [👆](https:\u002F\u002F1000projects.org\u002Fprojects\u002Fmachine-learning-projects) |\n| 64.   | 11个带有代码的计算机视觉项目                            | [👆](https:\u002F\u002Fgithub.com\u002Fakshaybhatia10\u002FComputerVision-Projects) |\n| 65.   | 13个带有代码的计算机视觉项目                            | [👆](https:\u002F\u002Fgithub.com\u002Fanuragreddygv323\u002Fcomputer-vision-projects) |\n| 66.   | 13个酷炫的计算机视觉GitHub项目，给你灵感               | [👆](https:\u002F\u002Fmachinelearningknowledge.ai\u002Fcool-computer-vision-github-projects-to-inspire-you\u002F) |\n| 67.   | 开源计算机视觉项目（附教程）                            | [👆](https:\u002F\u002Fwww.theclickreader.com\u002Fopen-source-computer-vision-projects-with-tutorials\u002F) |\n| 68.   | 用Python实现的OpenCV计算机视觉项目                      | [👆](https:\u002F\u002Fgithub.com\u002FPacktPublishing\u002FOpenCV-Computer-Vision-Projects-with-Python) |\n| 69.   | 100多个计算机视觉算法实现                               | [👆](https:\u002F\u002Fgithub.com\u002Fgmalivenko\u002Fawesome-computer-vision-models) |\n| 70.   | 80多个计算机视觉学习代码                                 | [👆](https:\u002F\u002Fgithub.com\u002Fspmallick\u002Flearnopencv)                |\n| 71.   | 深度学习宝藏                                               | [👆](https:\u002F\u002Fgithub.com\u002Fkmario23\u002Fdeep-learning-drizzle)       |\n| 72    | 数据分析与机器学习项目                                  | [👆](https:\u002F\u002Fgithub.com\u002Frhiever\u002FData-Analysis-and-Machine-Learning-Projects) |\n| 73    | AI项目                                                  | [👆](https:\u002F\u002Fgithub.com\u002FStevenLei2017\u002FAI_projects)            |\n| 74    | Kaggle项目合集                                            | [👆](https:\u002F\u002Fgithub.com\u002Falexattia\u002FData-Science-Projects)      |\n| 75    | 独特的AI项目                                              | [👆](https:\u002F\u002Fgithub.com\u002Frobsalgado\u002Fpersonal_data_science_projects) |\n| 76    | 数据科学项目合集                                          | [👆](https:\u002F\u002Fgithub.com\u002Ftuangauss\u002FDataScienceProjects)        |\n| 77    | 高级数据科学项目                                          | [👆](https:\u002F\u002Fgithub.com\u002FTheCodex-Me\u002FProjects)                 |\n| 78    | 高深的深度学习和机器学习项目                              | [👆](https:\u002F\u002Fgithub.com\u002Fnitinkaushik01\u002FDeep_and_Machine_Learning_Projects) |\n| 79    | Kaggle上的数据科学项目                                    | [👆](https:\u002F\u002Fgithub.com\u002Falexattia\u002FData-Science-Projects)      |\n| 80    | 自动深度学习项目                                          | [👆](https:\u002F\u002Fgithub.com\u002FD-X-Y\u002FAutoDL-Projects)                |\n| 81    | 180个机器学习项目                                        | [👆](https:\u002F\u002Fmedium.com\u002Fcoders-camp\u002F180-data-science-and-machine-learning-projects-with-python-6191bc7b9db9) |\n| 82    | 令人惊叹的黑客松项目合集                                | [👆](https:\u002F\u002Fgithub.com\u002Fanalyticsindiamagazine\u002FMachineHack\u002Ftree\u002Fmaster\u002FHackathon_Solutions) |\n| 83    | 优秀的NLP项目创意                                        | [👆](https:\u002F\u002Fnirantk.com\u002Fawesome-project-ideas\u002F)              |\n| 84    | 12个NLP项目                                              | [👆](https:\u002F\u002Fgithub.com\u002Fgaoisbest\u002FNLP-Projects)               |\n| 85    | 高级NLP项目                                               | [👆](https:\u002F\u002Fgithub.com\u002FPacktPublishing\u002FAdvanced-NLP-Projects-with-TensorFlow-2.0) |\n| 86    | 6个令人惊叹的NLP项目                                    | [👆](https:\u002F\u002Fgithub.com\u002Fanujvyas\u002FNatural-Language-Processing-Projects) |\n| 87    | NLP初学者项目                                            | [👆](https:\u002F\u002Fgithub.com\u002Fpositivepeng\u002Fnlp-beginner-projects)   |\n| 88    | PwC合集中的论文与代码                                    | [👆](https:\u002F\u002Fgithub.com\u002Fzziz\u002Fpwc)                             |\n| 89    | SOTA模型（最先进成果）                                    | [👆](https:\u002F\u002Fgithub.com\u002FRedditSota\u002Fstate-of-the-art-result-for-machine-learning-problems) |\n| 90    | 最佳AI论文                                                | [👆](https:\u002F\u002Fgithub.com\u002Flouisfb01\u002FBest_AI_paper_2020)         |\n| 91    | 生成对抗网络                                              | [👆](https:\u002F\u002Fgithub.com\u002Fzhangqianhui\u002FAdversarialNetsPapers)   |\n| 92    | 带有代码的计算机视觉论文                                | [👆](https:\u002F\u002Fgithub.com\u002FDWCTOD\u002FCVPR2022-Papers-with-Code-Demo) |\n| 93    | 带有代码的NILMS论文                                       | [👆](https:\u002F\u002Fgithub.com\u002Fklemenjak\u002Fnilm-papers-with-code)      |\n| 94    | 3D计算机视觉研究项目                                     | [👆](https:\u002F\u002Fgithub.com\u002FTom-Hardy-3D-Vision-Workshop\u002Fawesome-3D-vision) |\n| 95    | NLP和计算机视觉项目合集                                  | [👆](https:\u002F\u002Fgithub.com\u002FNELSONZHAO\u002Fzhihu)                     |\n| 96    | Udacity的计算机视觉项目合集                              | [👆](https:\u002F\u002Fgithub.com\u002FBjarten\u002Fcomputer-vision-ND)           |\n| 97    | 从零到英雄的TensorFlow教程                                | [👆](https:\u002F\u002Fgithub.com\u002Fmrdbourke\u002Ftensorflow-deep-learning)   |\n| 98    | 生产环境中的深度学习                                      | [👆](https:\u002F\u002Fgithub.com\u002FThe-AI-Summer\u002FDeep-Learning-In-Production) |\n| 99    | GANs合集                                                  | [👆](https:\u002F\u002Fgithub.com\u002FThe-AI-Summer\u002FGANs-in-Computer-Vision) |\n| 100   | 时间序列项目代码                                          | [👆](https:\u002F\u002Fgithub.com\u002Fdeshpandenu\u002FTime-Series-Forecasting-of-Amazon-Stock-Prices-using-Neural-Networks-LSTM-and-GAN-) |\n| 101   | 12个机器学习目标检测项目                                  | [👆](https:\u002F\u002Famankharwal.medium.com\u002F12-machine-learning-projects-on-object-detection-46b32adc3c37) |\n| 102   | 20个用Python实现的NLP项目                                  | [👆](https:\u002F\u002Fmedium.coders-camp\u002F20-machine-learning-projects-on-nlp-582effe73b9c) |\n| 103   | 深度学习、ML、计算机视觉和NLP的学习资料                   | [👆](https:\u002F\u002Fgithub.com\u002Fkmario23\u002Fdeep-learning-drizzle)       |\n\n***更多项目列表即将推出...!!!***\n\n---","# 500+ AI 项目合集快速上手指南\n\n本仓库并非单一的可安装软件包，而是一个精选的 **AI、机器学习、深度学习、计算机视觉和 NLP 项目资源索引列表**。它汇集了 500+ 个带有源代码的项目链接、教程和数据集。\n\n以下指南将帮助你如何高效利用此资源库开始你的 AI 学习与实践。\n\n## 环境准备\n\n由于列表中包含不同领域（如 CV、NLP、Time Series）的独立项目，每个项目的具体依赖可能不同。建议准备一个通用的 Python 数据科学开发环境。\n\n### 系统要求\n- **操作系统**: Windows, macOS, 或 Linux\n- **Python 版本**: 推荐 Python 3.8 - 3.10 (部分旧项目可能依赖 3.6\u002F3.7，新项目建议 3.9+)\n- **硬件**: 建议配备 NVIDIA GPU 以运行深度学习项目（非必须，但能显著加速训练）\n\n### 前置依赖\n在克隆本仓库后，你可以根据感兴趣的具体项目链接，单独配置环境。以下是通用的基础数据科学栈安装命令：\n\n```bash\n# 推荐使用 conda 创建独立环境\nconda create -n ai-projects python=3.9\nconda activate ai-projects\n\n# 安装核心基础库\npip install numpy pandas matplotlib seaborn scikit-learn jupyterlab\n\n# 安装深度学习框架 (根据项目需求选择其一或全部)\npip install torch torchvision torchaudio --index-url https:\u002F\u002Fdownload.pytorch.org\u002Fwhl\u002Fcu118\npip install tensorflow keras\n\n# 安装计算机视觉库\npip install opencv-python pillow\n\n# 安装 NLP 库\npip install nltk spacy transformers datasets\n```\n\n> **国内加速提示**：\n> 如果使用 `pip` 下载缓慢，建议使用清华或阿里镜像源：\n> ```bash\n> pip install \u003Cpackage_name> -i https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple\n> ```\n\n## 安装步骤\n\n本仓库本身只需克隆到本地即可浏览目录结构。\n\n1. **克隆仓库**\n   ```bash\n   git clone https:\u002F\u002Fgithub.com\u002Fashishpatel26\u002F500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code.git\n   ```\n\n2. **进入目录**\n   ```bash\n   cd 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code\n   ```\n\n3. **浏览项目列表**\n   打开根目录下的 `README.md` 文件（或在 GitHub 网页端查看），其中包含了分类清晰的表格，列出了项目名称和对应的代码仓库\u002F教程链接。\n\n## 基本使用\n\n本工具的核心用法是\"**检索 -> 跳转 -> 复现**\"。\n\n### 1. 查找感兴趣的项目\n在 `README.md` 的表格中，根据技术领域查找项目。例如：\n- **计算机视觉**: 搜索 \"Computer Vision\" 或查看第 1, 20, 64-70 项。\n- **自然语言处理**: 搜索 \"NLP\" 或查看第 2, 16, 23, 39, 58 项。\n- **实战预测**: 查看 \"Time Series Forecasting\" (第 4 项) 或 \"Future Prediction\" (第 10 项)。\n\n### 2. 获取具体项目代码\n点击表格中对应的链接（👆图标），这将带你前往具体的 GitHub 仓库、Medium 文章或教程页面。\n\n**示例：复现一个情感分析项目**\n假设你选择了列表中的第 16 项 \"6 Sentimental Analysis Projects with python\"：\n\n1. 点击链接进入目标页面。\n2. 找到该具体项目的源码仓库并克隆（假设目标仓库为 `sentiment-project`）：\n   ```bash\n   git clone https:\u002F\u002Fgithub.com\u002F目标作者\u002Fsentiment-project.git\n   cd sentiment-project\n   ```\n3. 安装该项目特定的依赖（通常目标仓库会有自己的 `requirements.txt`）：\n   ```bash\n   pip install -r requirements.txt\n   ```\n4. 运行示例代码：\n   ```bash\n   python main.py\n   # 或者运行 Jupyter Notebook\n   jupyter notebook analysis.ipynb\n   ```\n\n### 3. 贡献与更新\n该列表持续更新。如果你发现了新的优质项目或发现链接失效，可以通过 Pull Request 贡献回主仓库：\n\n```bash\n#  Fork 仓库后，修改 README.md 添加新链接\ngit add README.md\ngit commit -m \"Add new NLP project link\"\ngit push origin main\n```\n\n通过这种方式，你可以将这个索引作为起点，深入探索数百个高质量的 AI 实战案例。","一名刚入行的数据科学实习生需要在两周内完成一个包含情感分析和推荐系统的毕业项目，但缺乏明确的项目选题方向和可参考的代码框架。\n\n### 没有 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code 时\n- **选题迷茫耗时**：在海量教程中盲目搜索，花费数天时间仍无法确定适合初学者且具备完整代码的项目主题。\n- **代码复现困难**：找到的示例往往只有理论讲解或缺少关键数据处理步骤，导致环境配置和模型调试频频报错，进度停滞。\n- **知识体系碎片化**：只能零散地学习分类或回归算法，缺乏涵盖计算机视觉、NLP 等多领域的系统性项目清单来构建完整技能树。\n- **作品集单薄**：因时间紧迫只能完成一个简易 Demo，难以展示多样化的技术栈，导致求职简历缺乏竞争力。\n\n### 使用 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code 后\n- **精准锁定选题**：直接查阅列表中\"6 个 Python 情感分析项目”和\"4 个推荐系统项目”，迅速选定两个高匹配度题目并启动开发。\n- **全流程代码参考**：利用项目中提供的已测试源码，快速理解从数据清洗到模型部署的完整逻辑，将调试时间从几天缩短至几小时。\n- **系统化技能拓展**：按列表指引依次攻克时间序列预测和无监督学习等模块，在短时间内建立起覆盖机器学习全领域的实战经验。\n- **高质量作品交付**：基于成熟的代码框架优化出功能完善的双系统项目，显著提升了作品集的技术深度和可视化效果。\n\n500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code 通过提供经过验证的多样化项目库，将学习者从“找代码”的低效循环中解放出来，使其能专注于算法优化与业务逻辑的创新。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fashishpatel26_500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code_04deb5d4.gif","ashishpatel26","Ashish Patel","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002Fashishpatel26_9e4e7549.jpg","AI Researcher & Principal Architect AI\u002FML & Data Science at Oracle\r\n| xIBMers | Rank 3 Kaggle Kernel Master","Oracle | xIBMers","Ahmedabad","shriganesh.patel@gmail.com",null,"https:\u002F\u002Fmedium.com\u002Fml-research-lab","https:\u002F\u002Fgithub.com\u002Fashishpatel26",32832,7031,"2026-04-13T23:36:35",1,"","未说明",{"notes":90,"python":88,"dependencies":91},"该仓库并非单一的可执行 AI 工具，而是一个包含 500+ 个机器学习、深度学习、计算机视觉和 NLP 项目链接的资源列表（Awesome List）。每个链接指向独立的项目、教程或数据集，因此没有统一的运行环境、依赖库或硬件需求。用户需根据列表中具体选择的项目，查阅其各自仓库的 README 以获取相应的环境配置信息。",[],[93,15,35,14,16],"其他",[95,96,97,98,99,100,101,102,103,104,105,106,107],"awesome","machine-learning","deep-learning","machine-learning-projects","deep-learning-project","computer-vision-project","nlp-projects","artificial-intelligence-projects","python","artificial-intelligence","data-science","computer-vision","nlp","2026-03-27T02:49:30.150509","2026-04-14T12:26:53.276192",[],[]]