├── README_ch.md └── README.md /README_ch.md: -------------------------------------------------------------------------------- 1 | # Awesome AI List Guide 2 | 3 | 人工智能AI（也叫深度学习、机器学习）相关的清单向导！让你可以从清单开始找到你需要的！ 4 | 5 | **所有排名不分先后！！！** 6 | 7 | 欢迎PR！ 8 | 9 | [English](README.md) | [中文](README_ch.md) 10 | 11 | # 目录 12 | 13 | - [教程](#教程) 14 | - [CV](#CV) 15 | - [NLP](#NLP) 16 | - [Speech](#Speech) 17 | - [Others](#Others) 18 | 19 | 20 | 21 | ## 教程 22 | 23 | [awesome-for-beginners](https://github.com/MunGell/awesome-for-beginners)![](https://img.shields.io/github/stars/MunGell/awesome-for-beginners.svg?style=social): 很棒的适合初学者入门的项目列表。 24 | 25 | [Awesome production machine learning](https://github.com/EthicalML/awesome-production-machine-learning.git): 精选的开源库列表，用于部署、监控、版本和扩展您的机器学习 。 26 | 27 | [awesome-ai-infrastructures](https://github.com/1duo/awesome-ai-infrastructures) : 用于机器/深度学习训练和/或**生产**推理的真实 AI 基础架构**列表** 。 28 | 29 | [Production-Level-Deep-Learning](https://github.com/alirezadir/Production-Level-Deep-Learning): 构建实际生产级深度学习系统以部署到实际应用中的指南。 30 | 31 | [competition_baselines](https://github.com/LogicJake/competition_baselines) : 开源的各大比赛baseline 32 | 33 | [competition-baseline](https://github.com/datawhalechina/competition-baseline) : 数据科学竞赛知识、代码、思路 34 | 35 | [paper-reproduction-tutorials](https://github.com/PaddleEdu/paper-reproduction-tutorials) ： 论文复现技巧与PaddlePaddle优秀复现项目分享 36 | 37 | [awesome-mlops](https://github.com/visenger/awesome-mlops) :关于机器学习模型操作管理（建模全流程）的一个很棒的参考列表 38 | 39 | [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning) ：精心策划的机器学习框架、库和软件列表。 40 | 41 | [Learn-Data-Science-For-Free](https://github.com/therealsreehari/Learn-Data-Science-For-Free) ：这个仓库是分散在互联网上的不同资源的组合。制作这样一个存储库的原因是以顺序的方式组合所有有价值的资源，以便帮助每一个为数据科学寻找免费、结构化学习资源的初学者。 42 | 43 | [best-of-ml-python](https://github.com/ml-tooling/best-of-ml-python) ： 🏆 一个很棒的机器学习Python库的排名列表。每周更新一次。 44 | 45 | [build-your-own-x](https://github.com/danistefanovic/build-your-own-x) : 🤓 构建自己的X 46 | 47 | [tensorflow_practice](https://github.com/princewen/tensorflow_practice) : tensorflow实战练习，包括强化学习、推荐系统、nlp等 48 | 49 | [awesome-courses](https://github.com/prakhar1989/awesome-courses) : 📚 学习计算机科学的优秀大学课程列表！ 50 | 51 | [MT-Reading-List](https://github.com/THUNLP-MT/MT-Reading-List) : 清华自然语言处理集团维护的机器翻译阅读列表 52 | 53 | [cs-video-courses](https://github.com/Developer-Y/cs-video-courses) : 计算机科学课程和视频讲座列表。 54 | 55 | [machine-learning-surveys](https://github.com/metrofun/machine-learning-surveys) : 一份精心策划的机器学习调查、教程和书籍清单。 56 | 57 | [data-science-blogs](https://github.com/rushter/data-science-blogs) : 精心策划的数据科学博客列表 58 | 59 | [awesome-tensorflow](https://github.com/jtoy/awesome-tensorflow) : TensorFlow - 精心策划的专用资源清单 60 | 61 | [ds-cheatsheets](https://github.com/FavioVazquez/ds-cheatsheets) : List of Data Science Cheatsheets to rule the world 62 | 63 | [awesome-R](https://github.com/qinwf/awesome-R) : 一份精心策划的令人敬畏的R语言软件包、框架和软件清单。 64 | 65 | [awesome-youtubers](https://github.com/JoseDeFreitas/awesome-youtubers) : ▶️ 这是一个很棒的列表，里面有很多很棒的教授科技的YouTube。关于网络开发、计算机科学、机器学习、游戏开发、网络安全等的教程。 66 | 67 | [Book_List](https://github.com/mukeshmithrakumar/Book_List) : Python、机器学习、深度学习和数据科学书籍 68 | 69 | [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning) : 精心策划的深度学习教程、项目和社区列表 70 | 71 | [awesome-artificial-intelligence](https://github.com/owainlewis/awesome-artificial-intelligence) : 人工智能（AI）课程、书籍、视频讲座和论文的策划清单。 72 | 73 | [awesome-project-ideas](https://github.com/NirantK/awesome-project-ideas) : 机器学习、NLP、愿景、推荐系统项目理念策划清单 74 | 75 | [awesome-datascience](https://github.com/academic/awesome-datascience) : 📝 这是一个很棒的数据科学知识库，用于学习和解决真实世界的问题。 76 | 77 | [awesome-machine-learning-cn](https://github.com/jobbole/awesome-machine-learning-cn) : 机器学习资源大全中文版，包括机器学习领域的框架、库以及软件 78 | 79 | [Awesome-PyTorch-Chinese](https://github.com/INTERMT/Awesome-PyTorch-Chinese) : 【干货】史上最全的PyTorch学习资源汇总 80 | 81 | [awesome-AI-books](https://github.com/zslucky/awesome-AI-books) : 一些很棒的人工智能相关书籍和PDF供学习和下载，还应用一些娱乐模型进行学习 82 | 83 | [awesome-ml-courses](https://github.com/luspr/awesome-ml-courses) : 很棒的免费机器学习和AI课程，视频讲座。 84 | 85 | [awesome-ai-ml-dl](https://github.com/neomatrix369/awesome-ai-ml-dl) : 很棒的人工智能、机器学习和深度学习。研究笔记和这些主题的很棒的资源列表。 86 | 87 | [Awesome-Noah](https://github.com/AI-Sphere/Awesome-Noah) : AI圈Noah plan-AI数据竞赛Top可复现解决方案 88 | 89 | [my-awesome-AI-bookmarks](https://github.com/goodrahstar/my-awesome-AI-bookmarks) : 我的阅读、实现和人工智能、深度学习、机器学习的核心概念的精选列表，由世界上最优秀的人撰写。 90 | 91 | [awesome-DeepLearning](https://github.com/PaddlePaddle/awesome-DeepLearning) : 深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI 92 | 93 | [Machine-Learning-Collection](https://github.com/aladdinpersson/Machine-Learning-Collection) : 关于机器学习和深度学习的学习资源 94 | 95 | [DeepLearningSystem](https://github.com/chenzomi12/DeepLearningSystem) : 深度学习系统的核心原理：AI框架核心技术、AI编译器原理、推理系统、AI芯片。 96 | 97 | [free-programming-books](https://github.com/EbookFoundation/free-programming-books) : 📚 免费的编程书籍 98 | 99 | [research-method](https://github.com/secdr/research-method) : 论文写作与资料分享 100 | 101 | 102 | 103 | ## CV 104 | 105 | [awesome-hand-pose-estimation](https://github.com/xinghaochen/awesome-hand-pose-estimation): 手部姿势估计/跟踪方面的出色工作 106 | 107 | [CV-Backbones](https://github.com/huawei-noah/CV-Backbones) : 由华为诺亚方舟实验室开发的 CV 骨干网，包括 GhostNet、TinyNet 和 TNT。 108 | 109 | [SceneTextPapers](https://github.com/Jyouhou/SceneTextPapers.git): 跟踪场景文本检测和识别的最新进展：必读的高价值论文。 110 | 111 | [Awesome-GANs](https://github.com/kozistr/Awesome-GANs) : tensorflow的很棒的生成性对抗网络 112 | 113 | [OCR_DataSet](https://github.com/WenmuZhou/OCR_DataSet) : 收集并整理有关OCR的数据集并统一标注格式，以便实验需要 114 | 115 | [awesome-ocr](https://github.com/wanghaisheng/awesome-ocr) : 一份精心策划的有保证的OCR资源清单 116 | 117 | [Awesome-Table-Recognition](https://github.com/cv-small-snails/Awesome-Table-Recognition) : 专门用于表格识别的精心策划的资源列表 118 | 119 | [awesome-object-detection](https://github.com/amusi/awesome-object-detection) : 基于handong1587 github的超棒的目标检测 120 | 121 | [deep_learning_object_detection](https://github.com/hoya012/deep_learning_object_detection) : 使用深度学习的目标检测的论文列表。 122 | 123 | [awesome-captcha](https://github.com/ZYSzys/awesome-captcha) : 🔑 精心策划的超赞验证码库和破解工具列表。 124 | 125 | [image-to-image-papers](https://github.com/lzhbrian/image-to-image-papers) : 🦓<->🦒 🌃<->🌆 带有代码（不断更新）的图像到图像相关论文的集合 126 | 127 | [Deep-Learning-Papers-Reading-Roadmap](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap) : 为那些想学习深度学习的朋友提供一个论文阅读！ 128 | 129 | [benchmark_results](https://github.com/foolwood/benchmark_results) : 视觉跟踪论文清单 130 | 131 | [awesome_3DReconstruction_list](https://github.com/openMVG/awesome_3DReconstruction_list) : 图像三维重建相关的论文和资源。 132 | 133 | [the-gan-zoo](https://github.com/hindupuravinash/the-gan-zoo) : A list of all named GANs! 134 | 135 | [awesome-computer-vision](https://github.com/jbhuang0604/awesome-computer-vision) : 一份精心策划的优秀计算机视觉资源列表 136 | 137 | [multi-object-tracking-paper-list](https://github.com/SpyderXu/multi-object-tracking-paper-list) : 用于多目标跟踪的论文列表和源代码 138 | 139 | [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision) : 一份精心策划的计算机视觉深度学习资源清单 140 | 141 | [AdversarialNetsPapers](https://github.com/zhangqianhui/AdversarialNetsPapers) : 非常棒的关于生成性对抗网络的论文和代码清单 (gan) 142 | 143 | [awesome-lane-detection](https://github.com/amusi/awesome-lane-detection) : 车道检测的论文列表。 144 | 145 | [Paper_Reading_List](https://github.com/ArcherFMY/Paper_Reading_List) : 推荐的论文：计算机视觉和模式识别、人工智能、机器学习 146 | 147 | [awesome-network-embedding](https://github.com/chihming/awesome-network-embedding) : 一份精心策划的神经网络embedding技术的清单。 148 | 149 | [gans-awesome-applications](https://github.com/nashory/gans-awesome-applications) : 精心策划的GAN应用和演示列表 150 | 151 | [WeakSupervisedSegmentationList](https://github.com/JackieZhangdx/WeakSupervisedSegmentationList) : 该存储库包含state-of-art弱监督语义分割工作的列表 152 | 153 | [awesome-action-recognition](https://github.com/jinwchoi/awesome-action-recognition) : 行动识别和相关领域资源的策划清单 154 | 155 | [really-awesome-gan](https://github.com/nightrome/really-awesome-gan) : 关于生成性对抗（神经）网络的论文列表 156 | 157 | [awesome-panoptic-segmentation](https://github.com/Angzz/awesome-panoptic-segmentation) : 全景分割资源列表 158 | 159 | [Pedestrian-Attribute-Recognition-Paper-List](https://github.com/wangxiao5791509/Pedestrian-Attribute-Recognition-Paper-List) : 关于行人属性识别（PAR）和相关任务（模式识别2021）的论文列表 160 | 161 | [awesome-vqa](https://github.com/chingyaoc/awesome-vqa) : 视觉问答阅读清单 162 | 163 | [3D-Shape-Analysis-Paper-List](https://github.com/yinyunie/3D-Shape-Analysis-Paper-List) : 关于3D形状/场景分析的最新论文、库和数据集列表（按主题、更新）。 164 | 165 | [awesome-semantic-segmentation](https://github.com/mrgloom/awesome-semantic-segmentation) ：很棒的语义分割 166 | 167 | [Awesome-Crowd-Counting](https://github.com/gjy3035/Awesome-Crowd-Counting) : 很棒的人群计数 168 | 169 | [awesome-Face_Recognition](https://github.com/ChanChiChoi/awesome-Face_Recognition) : 关于人脸检测的论文；面部对齐；人脸识别、人脸识别、人脸验证和人脸表示；面部重建；人脸跟踪；面部超分辨率和面部去模糊；人脸生成与人脸合成；面部转移；人脸反欺骗；人脸检索； 170 | 171 | [AWESOME-FER](https://github.com/EvelynFan/AWESOME-FER) : 关注面部表情识别（FER）/面部动作单元（FAU）的顶级会议和期刊 172 | 173 | [Awesome-Gaze-Estimation](https://github.com/cvlab-uob/Awesome-Gaze-Estimation) : 很棒的人眼视线评估论文列表 174 | 175 | [awesome-ai-art-image-synthesis](https://github.com/altryne/awesome-ai-art-image-synthesis) : 一系列很棒的工具、想法、提示工程工具、colab、模型和助手，供提示设计师使用 aiArt 和图像合成。涵盖 Dalle2、MidJourney、StableDiffusion 和开源工具。 176 | 177 | [Diffusion-Models-Papers-Survey-Taxonomy](https://github.com/YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy) : 扩散模型的论文、调研和分类法 178 | 179 | [A-Survey-on-Generative-Diffusion-Model](https://github.com/chq1155/A-Survey-on-Generative-Diffusion-Model) : 扩散生成模型的精选列表，来自于一篇survey论文 180 | 181 | [Awesome-Face-Restoration](https://github.com/TaoWangzj/Awesome-Face-Restoration) : 关于面部恢复（人脸重建）方法的资源（论文、存储库等）的综合列表。 182 | 183 | [awesome-point-cloud-analysis](https://github.com/Yochengliu/awesome-point-cloud-analysis) : 点云分析（处理） 184 | 185 | [awesome-ai-painting](https://github.com/hua1995116/awesome-ai-painting) : AI绘画资料合集（包含国内外可使用平台、使用教程、参数教程、部署教程、业界新闻等等） 186 | 187 | [awesome-aigc](https://github.com/gongminmin/awesome-aigc) : 很棒的AIGC作品列表 188 | 189 | [awesome-llm-and-aigc](https://github.com/codingonion/awesome-llm-and-aigc) : 关于大型语言模型、视觉基础模型和人工智能生成内容的一些很棒的公共项目的集合。 190 | 191 | [awesome-text-to-video](https://github.com/jianzhnie/awesome-text-to-video) : 文本到视频生成/合成综述。 192 | 193 | [Awesome-AIGC-Tutorials](https://github.com/luban-agi/Awesome-AIGC-Tutorials) : 为大型语言模型、人工智能绘画等策划教程和资源。 194 | 195 | [Awesome-AIGC](https://github.com/wshzd/Awesome-AIGC) : AIGC资料汇总学习，持续更新...... 196 | 197 | 198 | 199 | ## NLP 200 | 201 | [nlp-tutorial](https://github.com/graykode/nlp-tutorial) : 面向深度学习研究人员的自然语言处理教程 202 | 203 | [language-resources](https://github.com/google/language-resources) : 初级自然语言处理的数据集和工具. 204 | 205 | [Summarization-Papers](https://github.com/xcfcode/Summarization-Papers) ：摘要任务的paper合集 206 | 207 | [CLUEDatasetSearch](https://github.com/CLUEbenchmark/CLUEDatasetSearch) ： 搜索所有中文NLP数据集，附常用英文NLP数据集。 208 | 209 | [nlpdemo-ch-wordlib](https://github.com/MrLi008/nlpdemo-ch-wordlib) : 中文各种词库 210 | 211 | [ChineseNLP](https://github.com/didi/ChineseNLP) : 中文自然语言处理各领域的数据集、SOTA结果 212 | 213 | [ChineseNLPCorpus](https://github.com/InsaneLife/ChineseNLPCorpus) : 中文自然语言处理数据集，平时做做实验的材料。 214 | 215 | [Chinese-Word-Vectors](https://github.com/Embedding/Chinese-Word-Vectors) : 100+ Chinese Word Vectors 上百种预训练中文词向量 216 | 217 | [ChineseNlpCorpus](https://github.com/SophonPlus/ChineseNlpCorpus) : 搜集、整理、发布 中文 自然语言处理 语料/数据集，与 有志之士 共同 促进 中文 自然语言处理 的 发展。 218 | 219 | [nlp-competitions-list-review](https://github.com/zhpmatrix/nlp-competitions-list-review) : 复盘所有NLP比赛的TOP方案，只关注NLP比赛，持续更新中！ 220 | 221 | [funNLP](https://github.com/fighting41love/funNLP) : 中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、历史名人词库、诗词词库、医学词库、饮食词库、法律词库、汽车词库、动物词库、中文聊天语料、中文谣言数据、百度中文问答数据集、句子相似度匹配算法集合、bert资源、文本生成&摘要相关工具、cocoNLP信息抽取工具、国内电话号码正则匹配、清华大学XLORE:中英文跨语言百科知识图谱、清华大学人工智能技术… 222 | 223 | [nlp_chinese_corpus](https://github.com/brightmart/nlp_chinese_corpus) : 大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP 224 | 225 | [awesome-2vec](https://github.com/MaxwellRebo/awesome-2vec) : 精心策划的向量化的embedding models列表 226 | 227 | [chatbot-list](https://github.com/lizhe2004/chatbot-list) : 行业内关于智能客服、聊天机器人的应用和架构、算法分享和介绍 228 | 229 | [awesome-chatbot-list](https://github.com/aceimnorstuvwxz/awesome-chatbot-list) : 深度学习聊天机器人资源集合 Awesome chatbot resource list 230 | 231 | [nmt-list](https://github.com/jonsafari/nmt-list) : 神经机器翻译相关实现的列表 232 | 233 | [Question-Generation-Paper-List](https://github.com/teacherpeterpan/Question-Generation-Paper-List) : 神经问题生成（NQG）必读论文汇总 234 | 235 | [awesome-nlp](https://github.com/keon/awesome-nlp) : 📖 一份精心策划的自然语言处理（NLP）资源清单 236 | 237 | [Style-Transfer-in-Text](https://github.com/fuzhenxin/Style-Transfer-in-Text) : 用于在文本中传输样式的论文列表 238 | 239 | [TG-Reading-List](https://github.com/THUNLP-MT/TG-Reading-List) : 清华自然语言处理团队维护的文本生成阅读列表。 240 | 241 | [awesome-sentence-embedding](https://github.com/Separius/awesome-sentence-embedding) : 一份精心策划的预训练句子和单词嵌入embedding模型列表 242 | 243 | [Awesome-Chinese-NLP](https://github.com/crownpku/Awesome-Chinese-NLP) : A curated list of resources for Chinese NLP 中文自然语言处理相关资料 244 | 245 | [*awesome*_Chinese_medical_*NLP*](https://github.com/GanjinZero/awesome_Chinese_medical_NLP) : 中文医学NLP公开资源整理：术语集/语料库/词向量/预训练模型/知识图谱/命名实体识别/QA/信息抽取/模型/论文/etc 246 | 247 | [awesome-dl4nlp](https://github.com/brianspiering/awesome-dl4nlp) : 一份精心策划的自然语言处理资源深度学习清单 248 | 249 | [Awesome-Korean-NLP](https://github.com/datanada/Awesome-Korean-NLP) : 韩语自然语言处理（NLP）资源的精选列表 250 | 251 | [awesome-bert-nlp](https://github.com/cedrickchee/awesome-bert-nlp) : 一份精心策划的NLP资源清单，重点介绍了BERT、注意机制、转换网络和迁移学习。 252 | 253 | [awesome-knowledge-graph](https://github.com/husthuke/awesome-knowledge-graph) : 整理知识图谱相关学习资料 254 | 255 | [Task-Oriented-Dialogue-Research-Progress-Survey](https://github.com/AtmaHou/Task-Oriented-Dialogue-Research-Progress-Survey) : 关于面向任务的对话的数据集和方法调查，包括最近的数据集和 SOTA 排行榜。 256 | 257 | [Text_Classification](https://github.com/kk7nc/Text_Classification) : 文本分类算法综述 258 | 259 | [awesome-punctuator](https://github.com/bigcash/awesome-punctuator) : 很棒的标点重建的精选列表 260 | 261 | [text-classification-surveys](https://github.com/xiaoqian19940510/text-classification-surveys) : 文本分类资源汇总，包括深度学习文本分类模型 262 | 263 | [awesome_Chinese_medical_NLP](https://github.com/GanjinZero/awesome_Chinese_medical_NLP) : 中文医学NLP公开资源整理：术语集/语料库/词向量/预训练模型/知识图谱/命名实体识别/QA/信息抽取/模型/论文/etc 264 | 265 | [Awesome-LLM](https://github.com/Hannibal046/Awesome-LLM) : Awesome-LLM: 大语言模型列表 266 | 267 | [Prompt-Engineering-Guide](https://github.com/dair-ai/Prompt-Engineering-Guide) : 提示工程向导、论文、教程和资源 268 | 269 | [PromptPapers](https://github.com/thunlp/PromptPapers) : 必读的关于预先训练的语言模型的基于提示的调优的论文。 270 | 271 | [awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts) : ChatGPT提示策略 272 | 273 | [awesome-chatgpt-prompts-zh](https://github.com/PlexPt/awesome-chatgpt-prompts-zh) : ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。 274 | 275 | [awesome-gpt3](https://github.com/elyase/awesome-gpt3) : Awesome GPT-3 是[OpenAI GPT-3 API](https://openai.com/blog/openai-api/)的一系列的样例演示和文章。 276 | 277 | [Awesome-ChatGPT](https://github.com/dalinvip/Awesome-ChatGPT) : ChatGPT资料汇总学习，持续更新...... 278 | 279 | [awesome-open-gpt](https://github.com/EwingYangs/awesome-open-gpt) : Collection of Open Source Projects Related to GPT，GPT相关开源项目合集🚀、精选🔥🔥 280 | 281 | [awesome-chatgpt](https://github.com/humanloop/awesome-chatgpt) : 为ChatGPT和GPT-3编写的很棒的工具、演示和文档列表 282 | 283 | [awesome-gpt4](https://github.com/radi-cho/awesome-gpt4) : 有关GPT-4语言模型的提示、工具和资源的精心策划的列表。 284 | 285 | [Awesome-ChatGPT](https://github.com/runningcheese/Awesome-ChatGPT) : 奶酪清单！ChatGPT相关知识 286 | 287 | [awesome-gpt](https://github.com/formulahendry/awesome-gpt) : 与GPT、ChatGPT、OpenAI、LLM等相关的精彩项目和资源的列表。 288 | 289 | [awesome-instruction-dataset](https://github.com/yaodongC/awesome-instruction-dataset) : 一个开源数据集的集合，用于训练LLM之后的指令微调（ChatGPT、LLaMA、Alpaca） 290 | 291 | [LLMSurvey](https://github.com/RUCAIBox/LLMSurvey) : 调查论文“大型语言模型调查”的官方GitHub页面。 292 | 293 | [awesome-langchain](https://github.com/kyrolabs/awesome-langchain) : 很棒的工具和项目列表与很棒的LangChain框架 294 | 295 | [awesome-pretrained-chinese-nlp-models](https://github.com/lonePatient/awesome-pretrained-chinese-nlp-models) : 高质量中文预训练模型&大模型&多模态模型&大语言模型集合 296 | 297 | [Awesome-Multimodal-Large-Language-Models](https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models) : 关于多模态大语言模型的最新论文和数据集及其评估。 298 | 299 | [awesome-LLMs-In-China](https://github.com/wgwang/awesome-LLMs-In-China) : 中国大模型 300 | 301 | [awesome-open-foundation-models](https://github.com/wgwang/awesome-open-foundation-models) : 开源开放的基础大模型列表 302 | 303 | [awesome-LLM-benchmarks](https://github.com/wgwang/awesome-LLM-benchmarks) : 大模型评测数据集和工具大全，涵盖文本、代码、图像、声音、视频以及跨模态等。 304 | 305 | [Awesome-Chinese-LLM](https://github.com/HqWu-HITCS/Awesome-Chinese-LLM) : 整理开源的中文大语言模型，以规模较小、可私有化部署、训练成本较低的模型为主，包括底座模型，垂直领域微调及应用，数据集与教程等。 306 | 307 | [Awesome-Domain-LLM](https://github.com/luban-agi/Awesome-Domain-LLM) : 收集和梳理垂直领域的开源模型、数据集及评测基准。 308 | 309 | [DecryptPrompt](https://github.com/DSXiangLi/DecryptPrompt) : 总结Prompt&LLM论文，开源数据&模型，AIGC应用 310 | 311 | [Awesome-Open-domain-Dialogue-Models](https://github.com/cingtiye/Awesome-Open-domain-Dialogue-Models) : Awesome Open-domain Dialogue Models，高质量开放域对话模型集合 312 | 313 | [LLMDataHub](https://github.com/Zjh-819/LLMDataHub) : 趋势指令微调数据集（LLM的SFT数据集、PT数据集、RLHF数据集）的快速指南 314 | 315 | [NLPer-Arsenal](https://github.com/TingFree/NLPer-Arsenal) : 收录NLP竞赛策略实现、各任务baseline、相关竞赛经验贴（当前赛事、往期赛事、训练赛）、NLP会议时间、常用自媒体、GPU推荐等 316 | 317 | [awesome-llm-apps](https://github.com/Shubhamsaboo/awesome-llm-apps) : 使用OpenAI、Anthropic、Gemini和开源模型的RAG的出色LLM应用程序集合。 318 | 319 | [llm-app](https://github.com/pathwaycom/llm-app) : 企业级动态RAG。已准备好使用Docker运行，⚡与Sharepoint、Google Drive、S3、Kafka、PostgreSQL、实时数据API等同步。 320 | 321 | [Awesome-LLM-RAG-Application](https://github.com/lizhe2004/Awesome-LLM-RAG-Application) : 基于RAG的LLM应用资源 322 | 323 | [Awesome-Text2SQL](https://github.com/eosphoros-ai/Awesome-Text2SQL) : 这里收集了针对大型语言模型、Text2SQL、[Text2DSL](https://github.com/eosphoros-ai/Awesome-Text2SQL/blob/main/Text2DSL.md)、 [Text2API](https://github.com/eosphoros-ai/Awesome-Text2SQL/blob/main/Text2API.md)、 [Text2Vis](https://github.com/eosphoros-ai/Awesome-Text2SQL/blob/main/Text2Vis.md) 等的精选教程和资源。 324 | 325 | [NL2SQL](https://github.com/yechens/NL2SQL) : Text2SQL 语义解析数据集、解决方案、paper资源整合项目 326 | 327 | [awesome-chatgpt-dataset](https://github.com/voidful/awesome-chatgpt-dataset) : 释放LLM的力量：探索这些数据集来训练你自己的ChatGPT！ 328 | 329 | [Awesome-LLM-Reasoning](https://github.com/atfortes/Awesome-LLM-Reasoning) : 大语言模型中的reasoning ：论文和资源，包括思维链和 OpenAI o1 🍓 330 | 331 | [Awesome-LLM-Strawberry](https://github.com/hijkzzz/Awesome-LLM-Strawberry) : 大语言模型LLM的论文、博客和项目的集合，重点关注OpenAI o1和 reasoning 技术。 332 | 333 | [Awesome-LLMOps](https://github.com/tensorchord/Awesome-LLMOps) : 为开发人员精心策划的最佳LLMOps部署推理运维工具列表 334 | 335 | [awesome-LLM-resourses](https://github.com/WangRongsheng/awesome-LLM-resourses) : 🧑‍🚀 全世界最好的LLM资料总结 | Summary of the world's best LLM resources. 336 | 337 | [Awesome-LLM-Robotics](https://github.com/GT-RIPL/Awesome-LLM-Robotics) : 使用大型语言/多模态模型进行机器人/强化学习RL的论文综合列表，包括论文、代码和相关网站 338 | 339 | [Awesome-LLM-Inference](https://github.com/DefTruth/Awesome-LLM-Inference) : 📖精选的Awesome LLM推理论文列表，包括代码、TensorRT LLM、vLLM、流式LLM、AWQ、SmoothQuant、WINT8/4、连续批处理、FlashAttention、PagedAttention等。 340 | 341 | [Awesome-LLM-RAG](https://github.com/jxzhangjhu/Awesome-LLM-RAG) : Awesome LLM RAG：大型语言模型中高级检索增强生成（RAG）的精选列表 342 | 343 | [Awesome-LLM-Compression](https://github.com/HuangOwen/Awesome-LLM-Compression) : 很棒的LLM模型压缩研究论文和工具。 344 | 345 | [Awesome-LLMs-on-device](https://github.com/NexaAI/Awesome-LLMs-on-device) : 端侧设备上出色的LLMs：综合调查 346 | 347 | [Awesome-LLMs-Datasets](https://github.com/lmmlzn/Awesome-LLMs-Datasets) : 总结现有的代表性LLM文本数据集。 348 | 349 | [awesome-ml](https://github.com/underlines/awesome-ml) : 有用的LLM/分析/数据科学资源精选列表 350 | 351 | [awesome-llm-security](https://github.com/corca-ai/awesome-llm-security) : 一系列关于LLM Security大模型安全的出色工具、文档和项目。 352 | 353 | [Awesome-LLM4AD](https://github.com/Thinklab-SJTU/Awesome-LLM4AD) : 精心策划的自动驾驶大模型LLM资源列表 354 | 355 | [awesome-llm-powered-agent](https://github.com/hyp1231/awesome-llm-powered-agent) : 关于LLM驱动的Agent的很棒的列表：论文/转载/博客 356 | 357 | [awesome-llm-json](https://github.com/imaurer/awesome-llm-json) : 通过函数调用、工具、CFG使用LLM生成JSON的资源列表。图书馆、模型、笔记本等。 358 | 359 | [Awesome-Code-LLM](https://github.com/codefuse-ai/Awesome-Code-LLM) : 代码和相关数据集的大语言建模研究精选列表。 360 | 361 | [awesome-llm-interpretability](https://github.com/JShollaj/awesome-llm-interpretability) : 大型语言模型（LLM）可解释性资源的精选列表。 362 | 363 | [Awesome-Graph-LLM](https://github.com/XiaoxinHe/Awesome-Graph-LLM) : 关于图相关LLM的一系列精彩内容。 364 | 365 | [Awesome-GPT-Agents](https://github.com/fr0gger/Awesome-GPT-Agents) : 精心策划的网络安全的大模型GPT Agent列表 366 | 367 | [LLM4Rec-Awesome-Papers](https://github.com/WLiK/LLM4Rec-Awesome-Papers) : 大型语言模型推荐系统（LLM）的优秀论文和资源列表。 368 | 369 | [Awesome-LLM-KG](https://github.com/RManLuo/Awesome-LLM-KG) : 关于整合大语言模型LLM和知识图谱的精彩论文 370 | 371 | [awesome_LLMs_interview_notes](https://github.com/jackaduma/awesome_LLMs_interview_notes) : LLMs interview notes and answers:该仓库主要记录大模型（LLMs）算法工程师相关的面试题和参考答案 372 | 373 | 374 | 375 | ## Speech 376 | 377 | [awesome-speech-recognition-speech-synthesis-papers](https://github.com/zzw922cn/awesome-speech-recognition-speech-synthesis-papers) ： 自动语音识别（ASR）、说话人确认、语音合成、文本到语音（TTS）、语言建模、歌唱语音合成（SVS）、语音转换（VC） 378 | 379 | [Speech-Separation-Paper-Tutorial](https://github.com/JusperLee/Speech-Separation-Paper-Tutorial) ： 基于神经网络的语音分离的必读论文 380 | 381 | [speech-recognition-papers](https://github.com/wenet-e2e/speech-recognition-papers): 面向工业端到端语音识别的热点方向 382 | 383 | [awesome-data-augmentation](https://github.com/CrazyVertigo/awesome-data-augmentation)![](https://img.shields.io/github/stars/CrazyVertigo/awesome-data-augmentation.svg?style=social)： 这是一个关于数据增强的很棒的方法列表。 384 | 385 | [Awesome-SLP](https://github.com/BenSaunders27/Awesome-SLP.git): 精选的手语产品工作清单 。 386 | 387 | [Awesome-SLU-Survey](https://github.com/yizhen20133868/Awesome-SLU-Survey) ：口语理解研究综述：最新进展和新前沿 388 | 389 | [speech_dataset](https://github.com/double22a/speech_dataset): 语音识别数据集 390 | 391 | [awesome_OpenSetRecognition_list](https://github.com/iCGY96/awesome_OpenSetRecognition_list): 开放集识别、 分布外 (OoD) 泛化 、 开放集域适应和 开放世界识别 相关的论文和资源的策划列表 392 | 393 | [Awesome-Speech-Enhancement](https://github.com/nanahou/Awesome-Speech-Enhancement) ：为语音增强研究人员和实践者提供的教程。本项目的目的是整理全世界用于语音增强的资源，使其普遍可用。 394 | 395 | [awesome-speech-enhancement](https://github.com/WenzheLiu-Speech/awesome-speech-enhancement) : 语音增强，语音分离，声源定位 396 | 397 | [speech_data_augment](https://github.com/zzpDapeng/speech_data_augment) : 语音数据增强算法总结 398 | 399 | [wer_are_we](https://github.com/syhw/wer_are_we) : 尝试跟踪语音识别的最新研究成果（参考文献）。 400 | 401 | [awesome-diarization](https://github.com/wq2012/awesome-diarization) : 这是一份精心策划的说话人分割聚类（也叫声纹分割聚类、说话人日志）列表，包括论文、库、数据集和其他资源。 402 | 403 | [awesome-audio-visualization](https://github.com/willianjusten/awesome-audio-visualization) : 关于音频可视化的策划列表。 404 | 405 | [awesome-deep-learning-music](https://github.com/ybayle/awesome-deep-learning-music) : 关于音乐领域的深度学习相关的文章列表 406 | 407 | [speech-language-processing](https://github.com/edobashira/speech-language-processing) : 语音和自然语言处理资源的精选列表 408 | 409 | [speech-synthesis-paper](https://github.com/wenet-e2e/speech-synthesis-paper) : 语音合成论文列表。 410 | 411 | [SpeechAlgorithms](https://github.com/Ryuk17/SpeechAlgorithms) : 语音算法集合 412 | 413 | [awesome-vad](https://github.com/bigcash/awesome-vad) : 语音端点检测 414 | 415 | [SER-datasets](https://github.com/SuperKogito/SER-datasets) : 用于语音中情绪识别/检测的数据集集合。 416 | 417 | [awesome-openai-whisper](https://github.com/ancs21/awesome-openai-whisper) : OpenAI's Whisper的ASR语音识别相关的精彩集合 418 | 419 | [Tutorial_Separation](https://github.com/gemengtju/Tutorial_Separation) : 总结了语音分离和说话人抽取任务的教程、数据集、论文、代码和工具。 420 | 421 | [open-speech-corpora](https://github.com/coqui-ai/open-speech-corpora) : 💎ASR、TTS和其他语音技术的可访问的语音语料库、语音数据集列表 422 | 423 | [awesome-vits](https://github.com/34j/awesome-vits) : VITS相关的代码库 424 | 425 | [Awesome-Text-to-Speech-TTS](https://github.com/TouchSky-Lab/Awesome-Text-to-Speech-TTS) : TTS 426 | 427 | [awesome-tts-samples](https://github.com/seungwonpark/awesome-tts-samples) : TTS相关的论文或代码库 428 | 429 | [awesome-disfluency-detection](https://github.com/pariajm/awesome-disfluency-detection) : 非常棒的文本不流畅检测，包括代码和论文，可以对ASR的结果结果进行文本流畅处理。 430 | 431 | [WeDataset](https://github.com/wenet-e2e/wenet/issues/2094): 开源语音数据集列表+爬虫资源列表 432 | 433 | 434 | 435 | ## Others 436 | 437 | [anomaly-detection-resources](https://github.com/yzhao062/anomaly-detection-resources) : 异常检测相关书籍、论文、视频和工具箱 438 | 439 | [awesome-anomaly-detection](https://github.com/hoya012/awesome-anomaly-detection) : 精心策划的异常检测资源列表 440 | 441 | [Surface-Defect-Detection](https://github.com/Charmve/Surface-Defect-Detection) : 不断总结开源数据集和表面缺陷研究领域的重要论文。 442 | 443 | [Awesome-Meta-Learning](https://github.com/sudharsan13296/Awesome-Meta-Learning) : 元学习（学习如何去学习）相关的论文、代码、书籍、博客、视频、数据集和其他资源的策划列表。 444 | 445 | [GitHub-Chinese-Top-Charts](https://github.com/GrowingGit/GitHub-Chinese-Top-Charts) : 🇨🇳 GitHub中文排行榜，各语言分离设置「软件 / 资料」榜单，精准定位中文好项目。各取所需，互不干扰，高效学习。 446 | 447 | [state-of-the-art-result-for-machine-learning-problems](https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems) : 该存储库为所有机器学习问题提供最先进的（SoTA）结果。我们尽最大努力使此存储库保持最新。如果您发现某个问题的SoTA结果已过期或缺失，请将其作为问题提出，或提交谷歌表格（包含以下信息：研究论文名称、数据集、指标、源代码和年份）。 448 | 449 | [PyTorchTricks](https://github.com/lartpang/PyTorchTricks) : pytorch的一些技巧... ⭐ 450 | 451 | [Awesome-pytorch-list-CNVersion](https://github.com/xavier-zy/Awesome-pytorch-list-CNVersion) : 厉害的Pytorch项目，翻译工作进行中...... 452 | 453 | [Awesome-pytorch-list](https://github.com/bharathgs/Awesome-pytorch-list) : github上pytorch相关内容的综合列表，如不同的模型、实现、帮助库、教程等。 454 | 455 | [deeplearning-models](https://github.com/rasbt/deeplearning-models) : 各种深度学习架构、模型和技巧的集合 456 | 457 | [awesome-data-labeling](https://github.com/heartexlabs/awesome-data-labeling) : 精心策划的优秀数据标注工具列表 458 | 459 | [Awesome-Learning-with-Label-Noise](https://github.com/subeeshvasu/Awesome-Learning-with-Label-Noise) : 一份精心策划的有噪声标注数据集下模型如何学习训练的资源清单 460 | 461 | [awesome-music-production](https://github.com/ad-si/awesome-music-production.git): 用于创建和分发音乐的软件、服务和资源的精选列表。 462 | 463 | [leetcode-master](https://github.com/youngyangyang04/leetcode-master) ： 《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀 464 | 465 | [awesome-python-login-model](https://github.com/Kr1s77/awesome-python-login-model) ： 😮python模拟登陆一些大型网站，还有一些简单的爬虫， 466 | 467 | [awesome-spider](https://github.com/facert/awesome-spider) : 爬虫集合 468 | 469 | [awesome-python](https://github.com/vinta/awesome-python) : 一份精心策划的优秀Python框架、库、软件和资源列表 470 | 471 | [awesome-remote-job](https://github.com/lukasz-madon/awesome-remote-job) : 精心策划的远程工作和资源列表。 472 | 473 | [public-apis](https://github.com/public-apis/public-apis) : 免费API的集合列表 474 | 475 | [Public-APIs](https://github.com/n0shake/Public-APIs) : 📚 来自网络的API公开列表。 476 | 477 | [public-api-lists](https://github.com/public-api-lists/public-api-lists) : 用于软件和web开发的免费API的集合列表🚀 478 | 479 | [lists](https://github.com/jnv/lists) : 在 GitHub 上整理的有用的、搞笑的和很棒的列表。 480 | 481 | [interview](https://github.com/Olshansk/interview) : 准备技术面试所需的一切 482 | 483 | [A-to-Z-Resources-for-Students](https://github.com/dipakkr/A-to-Z-Resources-for-Students) : ✅ 为大学生策划的资源清单 484 | 485 | [awesome-math](https://github.com/rossant/awesome-math) : 一份精心策划的数学资源清单 486 | 487 | [awesome-raspberry-pi](https://github.com/thibmaek/awesome-raspberry-pi) : 📝 这是一份精心策划的列表，其中包括很棒的树莓派工具、项目、图像和资源 488 | 489 | [science-based-games-list](https://github.com/stared/science-based-games-list) : 基于科学的游戏-合作列表 490 | 491 | [awesome-SLAM-list](https://github.com/OpenSLAM/awesome-SLAM-list) : awesome-SLAM-list 492 | 493 | [awesome-slam](https://github.com/kanster/awesome-slam) : 一份精心策划的很棒的SLAM教程、项目和社区列表。 494 | 495 | [SLAM-All-In-One](https://github.com/zhouyong1234/SLAM-All-In-One) : SLAM汇总，包括多传感器融合建图、定位、VIO系列、常用工具包、开源代码注释和公式推导、文章综述 496 | 497 | [awesome-robotics](https://github.com/kiloreux/awesome-robotics) : 非常棒的机器人资源列表 498 | 499 | [TopDeepLearning](https://github.com/aymericdamien/TopDeepLearning) : 深度学习相关的热门github项目列表 500 | 501 | [awesome-ai-residency](https://github.com/dangkhoasdc/awesome-ai-residency) : AI实习计划列表清单 502 | 503 | [ICRA2020-paper-list](https://github.com/PaoPaoRobot/ICRA2020-paper-list) : ICRA2020：2020年IEEE机器人与自动化国际会议。 504 | 505 | [RSPapers](https://github.com/hongleizhang/RSPapers) : 推荐系统的必读论文策划清单。 506 | 507 | [Awesome-Embedded](https://github.com/nhivp/Awesome-Embedded) : 一份精心策划的优秀嵌入式编程列表。 508 | 509 | [useful-computer-vision-phd-resources](https://github.com/hassony2/useful-computer-vision-phd-resources) : 对我的计算机视觉博士学位有用的资源列表 510 | 511 | [spatio-temporal-paper-list](https://github.com/Eilene/spatio-temporal-paper-list) : Spatio-temporal modeling 论文列表（主要是graph convolution相关) 512 | 513 | [awesome-self-supervised-learning](https://github.com/jason718/awesome-self-supervised-learning) : 精心策划的自监督方法列表 514 | 515 | [medical-imaging-datasets](https://github.com/sfikas/medical-imaging-datasets) : 医疗成像数据集列表。 516 | 517 | [awesome-roadmaps](https://github.com/liuchong/awesome-roadmaps) : 一份精心策划的学习路线图清单。 518 | 519 | [EEG-Datasets](https://github.com/meagmohit/EEG-Datasets) : 所有公共脑电图数据集的列表 520 | 521 | [MARL-Papers](https://github.com/LantaoYu/MARL-Papers) : 多智能体强化学习（MARL）论文列表 522 | 523 | [awesome-multimodal-ml](https://github.com/pliang279/awesome-multimodal-ml) : 多模态机器学习研究主题阅读清单 524 | 525 | [Awesome-Multimodal-Research](https://github.com/Eurus-Holmes/Awesome-Multimodal-Research) : 多模态相关研究的策划清单。 526 | 527 | [deep-reinforcement-learning-papers](https://github.com/junhyukoh/deep-reinforcement-learning-papers) : 关于深度强化学习的最新论文列表 528 | 529 | [awesome-machine-learning-interpretability](https://github.com/jphall663/awesome-machine-learning-interpretability) : 精心策划的机器学习可解释性资源列表。 530 | 531 | [awesome-fast-attention](https://github.com/Separius/awesome-fast-attention) : 高效注意力模块列表 532 | 533 | [deeplearning-biology](https://github.com/hussius/deeplearning-biology) : 生物学深度学习实现相关的清单 534 | 535 | [FreeML](https://github.com/Shujian2015/FreeML) : 数据科学/机器学习资源列表（大部分免费） 536 | 537 | [Paper-List](https://github.com/ConanCui/Paper-List) : 每天维护的在读论文的清单 538 | 539 | [awesome-jupyter](https://github.com/markusschanta/awesome-jupyter) : 精心策划的优秀Jupyter项目、图书馆和资源列表 540 | 541 | [the-incredible-pytorch](https://github.com/ritchieng/the-incredible-pytorch) : 不可思议的PyTorch：一份精心策划的关于PyTorch的教程、论文、项目、社区和更多内容的列表。 542 | 543 | [awesome-quant](https://github.com/wilsonfreitas/awesome-quant) : 为量化金融（Quant Finance）策划了一份非常棒的库、软件包和资源列表 544 | 545 | [awesome-quant](https://github.com/thuquant/awesome-quant) : 中国的Quant相关资源索引 546 | 547 | [awesome-community-detection](https://github.com/benedekrozemberczki/awesome-community-detection) : 一份经过策划的社区检测研究论文清单及其实现。 548 | 549 | [awesome-robotics-libraries](https://github.com/jslee02/awesome-robotics-libraries) : 😎 一份精心策划的机器人技术库和软件列表 550 | 551 | [awesome_time_series_in_python](https://github.com/MaxBenChrist/awesome_time_series_in_python) : 这个精心策划的列表包含用于时间序列分析的python包 552 | 553 | [awesome-rnn](https://github.com/kjw0612/awesome-rnn) : 递归神经网络——专门用于RNN的精心策划的资源列表 554 | 555 | [awesome-random-forest](https://github.com/kjw0612/awesome-random-forest) : 随机森林——关于随机森林的精选资源列表 556 | 557 | [awesome-adversarial-machine-learning](https://github.com/yenchenlin/awesome-adversarial-machine-learning) : 一份精心策划的很棒的对抗性机器学习资源列表 558 | 559 | [awesome-awesome](https://github.com/emijrp/awesome-awesome) : 这是一份精心策划的清单，里面有很多精彩的主题。 560 | 561 | [VR-Awesome](https://github.com/Vytek/VR-Awesome) : 很棒的VR相关列表 562 | 563 | [machine-learning-surveys](https://github.com/metrofun/machine-learning-surveys) : 一份精心策划的机器学习调查、综述、教程和书籍清单。 564 | 565 | [awesome-rl](https://github.com/aikorea/awesome-rl) : 强化学习资源列表 566 | 567 | [awesome-knowledge-distillation](https://github.com/dkozlov/awesome-knowledge-distillation) : 很棒的知识蒸馏 568 | 569 | [Awesome-Incremental-Learning](https://github.com/xialeiliu/Awesome-Incremental-Learning) : 很棒的增量学习/终身学习 570 | 571 | [awesome-graph-classification](https://github.com/benedekrozemberczki/awesome-graph-classification) : 一系列重要的图形嵌入、分类和表示学习论文及其实现。 572 | 573 | [Awesome-Transformer-Attention](https://github.com/cmhungsteve/Awesome-Transformer-Attention) ： Vision Transformer/注意力的最终综合论文列表，包括论文、代码和相关网站 574 | 575 | [awesome-public-datasets](https://github.com/awesomedata/awesome-public-datasets) : 高质量的公开数据集列表。 576 | 577 | [awesome-ai-in-finance](https://github.com/georgezouq/awesome-ai-in-finance) : 🔬 金融领域中很棒的机器学习策略和工具。 578 | 579 | [Awesome-explainable-AI](https://github.com/wangyongjie-ntu/Awesome-explainable-AI) : 可解释AI/ML研究材料集 580 | 581 | [Awesome-Federated-Learning](https://github.com/chaoyanghe/Awesome-Federated-Learning) : 很棒的联邦学习列表 582 | 583 | [Awesome-AI-Security](https://github.com/DeepSpaceHarbor/Awesome-AI-Security) : 人工智能安全资源精选列表，灵感来自于 [awesome-adversarial-machine-learning](https://github.com/yenchenlin/awesome-adversarial-machine-learning) & [awesome-ml-for-cybersecurity](https://github.com/jivoi/awesome-ml-for-cybersecurity). 584 | 585 | [awesome-deep-rl](https://github.com/tigerneil/awesome-deep-rl) : 深度强化学习和人工智能的未来。 586 | 587 | [awesome-fashion-ai](https://github.com/ayushidalmia/awesome-fashion-ai) : 一个存储库，用于整理和总结与时尚和电子商务相关的研究论文 588 | 589 | [awesome-blockchain-ai](https://github.com/steven2358/awesome-blockchain-ai) : 人工智能和机器学习的区块链项目精选列表 590 | 591 | [awesome-starcraftAI](https://github.com/SKTBrain/awesome-starcraftAI) : 专门用于星际争霸 AI 的精选资源列表。 592 | 593 | [awesome-game-ai](https://github.com/datamllab/awesome-game-ai) : 很棒的多智能体强化学习的游戏AI素材 594 | 595 | [awesome-feature-engineering](https://github.com/aikho/awesome-feature-engineering) : 专门用于机器学习的特征工程技术的资源列表 596 | 597 | [awesome-ai-usecases](https://github.com/JosPolfliet/awesome-ai-usecases) : 一系列很棒的且经过验证的人工智能用例和应用程序 598 | 599 | [lite.ai.toolkit](https://github.com/DefTruth/lite.ai.toolkit) : 一个lite C++工具包，包含了ONNXRuntime、NCNN、MNN和TNN的很棒的人工智能模型。YOLOX, YOLOP, YOLOv6, YOLOR, MODNet, YOLOX, YOLOv7, YOLOv5. MNN, NCNN, TNN, ONNXRuntime. 600 | 601 | [awesome-ai](https://github.com/hades217/awesome-ai) : 人工智能资源（课程、工具、应用程序、开源项目）的精选列表 602 | 603 | [500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code](https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code) : 500+人工智能机器学习深度学习计算机视觉NLP项目代码 604 | 605 | [knowledge-distillation-papers](https://github.com/lhyfst/knowledge-distillation-papers) : 知识蒸馏论文 606 | 607 | [Awesome_Continual-Lifelong-Incremental_learning](https://github.com/chengsilin/Awesome_Continual-Lifelong-Incremental_learning) : 持续增量学习 608 | 609 | [Awesome-Few-Shot-Class-Incremental-Learning](https://github.com/zhoudw-zdw/Awesome-Few-Shot-Class-Incremental-Learning) : 小样本持续增量学习 610 | 611 | [awesome-gcn](https://github.com/Jiakui/awesome-gcn) : 图卷积神经网络相关资源 612 | 613 | [Awesome-Deep-Graph-Clustering](https://github.com/yueliu1999/Awesome-Deep-Graph-Clustering) : 深度图聚类的SOTA集合，包括论文、代码、数据集 614 | 615 | [awesome-denovo-papers](https://github.com/asarigun/awesome-denovo-papers) : 全新药物设计的论文集合 616 | 617 | [awesome-lidar](https://github.com/szenergy/awesome-lidar) : 激光雷达列表。该列表包括激光雷达制造商、数据集、点云处理算法、点云框架和模拟器。 618 | 619 | [awesome-self-supervised-gnn](https://github.com/ChandlerBang/awesome-self-supervised-gnn) : 关于图形神经网络（GNN）的预训练和自监督学习的论文 620 | 621 | [ai-collection](https://github.com/ai-collection/ai-collection) : 生成式 AI 大观园 - 一组很棒的生成式 AI 应用程序 622 | 623 | [papers-we-love](https://github.com/papers-we-love/papers-we-love) : 大量来自计算机科学社区的论文，可供阅读和讨论。 624 | 625 | [Awesome-Autonomous-Driving](https://github.com/autodriving-heart/Awesome-Autonomous-Driving) : 自动驾驶 -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Awesome AI List Guide 2 | 3 | The guide of awesome list about **AI** ( a.k.a., **artificial intelligence**, **machine learning**, **deep learning**) 4 | 5 | **The list is in no particular order!!!** 6 | 7 | Pull requests are welcome! 8 | 9 | [English](README.md) | [中文](README_ch.md) 10 | 11 | # Table of Contents 12 | 13 | - [Tutorials](#Tutorials) 14 | - [CV](#CV) 15 | - [NLP](#NLP) 16 | - [Speech](#Speech) 17 | - [Others](#Others) 18 | 19 | 20 | 21 | ## Tutorials 22 | 23 | [awesome-for-beginners](https://github.com/MunGell/awesome-for-beginners): A list of awesome beginners-friendly projects. 24 | 25 | [Awesome production machine learning](https://github.com/EthicalML/awesome-production-machine-learning.git): A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning 26 | 27 | [awesome-ai-infrastructures](https://github.com/1duo/awesome-ai-infrastructures) : Infrastructures™ for Machine Learning Training/Inference in Production. 28 | 29 | [Production-Level-Deep-Learning](https://github.com/alirezadir/Production-Level-Deep-Learning): A guideline for building practical production-level deep learning systems to be deployed in real world applications. 30 | 31 | [competition_baselines](https://github.com/LogicJake/competition_baselines) : Open competition's baseline 32 | 33 | [competition-baseline](https://github.com/datawhalechina/competition-baseline) : Knowledge, code and ideas of data science competition 34 | 35 | [paper-reproduction-tutorials](https://github.com/PaddleEdu/paper-reproduction-tutorials) ： The skill of reproducing papers and sharing PaddlePaddle outstanding projects 36 | 37 | [awesome-mlops](https://github.com/visenger/awesome-mlops) : A curated list of references for MLOps 38 | 39 | [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning) ： A curated list of awesome Machine Learning frameworks, libraries and software. 40 | 41 | [Learn-Data-Science-For-Free](https://github.com/therealsreehari/Learn-Data-Science-For-Free) ： This repositary is a combination of different resources lying scattered all over the internet. The reason for making such an repositary is to combine all the valuable resources in a sequential manner, so that it helps every beginners who are in a search of free and structured learning resource for Data Science. For Constant Updates Follow me in … 42 | 43 | [best-of-ml-python](https://github.com/ml-tooling/best-of-ml-python) ： 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly. 44 | 45 | [build-your-own-x](https://github.com/danistefanovic/build-your-own-x) : 🤓 Build your own (insert technology here) 46 | 47 | [tensorflow_practice](https://github.com/princewen/tensorflow_practice) : Tensorflow practice, including reinforcement learning, recommendation system, NLP, etc 48 | 49 | [awesome-courses](https://github.com/prakhar1989/awesome-courses) : 📚 List of awesome university courses for learning Computer Science! 50 | 51 | [MT-Reading-List](https://github.com/THUNLP-MT/MT-Reading-List) : A machine translation reading list maintained by Tsinghua Natural Language Processing Group 52 | 53 | [cs-video-courses](https://github.com/Developer-Y/cs-video-courses) : List of Computer Science courses with video lectures. 54 | 55 | [machine-learning-surveys](https://github.com/metrofun/machine-learning-surveys) : A curated list of Machine Learning Surveys, Tutorials and Books. 56 | 57 | [data-science-blogs](https://github.com/rushter/data-science-blogs) : A curated list of data science blogs 58 | 59 | [awesome-tensorflow](https://github.com/jtoy/awesome-tensorflow) : TensorFlow - A curated list of dedicated resources 60 | 61 | [ds-cheatsheets](https://github.com/FavioVazquez/ds-cheatsheets) : List of Data Science Cheatsheets to rule the world 62 | 63 | [awesome-R](https://github.com/qinwf/awesome-R) : A curated list of awesome R packages, frameworks and software. 64 | 65 | [awesome-youtubers](https://github.com/JoseDeFreitas/awesome-youtubers) : ▶️ An awesome list of awesome YouTubers that teach about technology. Tutorials about web development, computer science, machine learning, game development, cybersecurity, and more. 66 | 67 | [Book_List](https://github.com/mukeshmithrakumar/Book_List) : Python, Machine Learning, Deep Learning and Data Science Books 68 | 69 | [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning) : A curated list of awesome Deep Learning tutorials, projects and communities. 70 | 71 | [awesome-artificial-intelligence](https://github.com/owainlewis/awesome-artificial-intelligence) : A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers. 72 | 73 | [awesome-project-ideas](https://github.com/NirantK/awesome-project-ideas) : Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas 74 | 75 | [awesome-datascience](https://github.com/academic/awesome-datascience) : 📝 An awesome Data Science repository to learn and apply for real world problems. 76 | 77 | [awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers) : The most cited deep learning papers 78 | 79 | [awesome-machine-learning-cn](https://github.com/jobbole/awesome-machine-learning-cn) : Machine learning resources of Chinese version, including the framework, library and software in the field of machine learning 80 | 81 | [Awesome-PyTorch-Chinese](https://github.com/INTERMT/Awesome-PyTorch-Chinese) : the most complete pytorch learning resources in history 82 | 83 | [awesome-AI-books](https://github.com/zslucky/awesome-AI-books) : Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning 84 | 85 | [awesome-ml-courses](https://github.com/luspr/awesome-ml-courses) : Awesome free machine learning and AI courses with video lectures. 86 | 87 | [awesome-ai-ml-dl](https://github.com/neomatrix369/awesome-ai-ml-dl) : Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics. 88 | 89 | [Awesome-Noah](https://github.com/AI-Sphere/Awesome-Noah) : Awesome Top Solution List of Excellent AI Competitions 90 | 91 | [my-awesome-AI-bookmarks](https://github.com/goodrahstar/my-awesome-AI-bookmarks) : Curated list of my reads, implementations and core concepts of Artificial Intelligence, Deep Learning, Machine Learning by best folk in the world. 92 | 93 | [awesome-DeepLearning](https://github.com/PaddlePaddle/awesome-DeepLearning) : The course, case and knowledge of Deep Learning and AI 94 | 95 | [Machine-Learning-Collection](https://github.com/aladdinpersson/Machine-Learning-Collection) : A resource for learning about Machine learning & Deep Learning 96 | 97 | [DeepLearningSystem](https://github.com/chenzomi12/DeepLearningSystem) : Deep Learning System core principles introduction. 98 | 99 | [free-programming-books](https://github.com/EbookFoundation/free-programming-books) : 📚 Freely available programming books 100 | 101 | [research-method](https://github.com/secdr/research-method) : Paper Writing and Resources Sharing 102 | 103 | 104 | 105 | ## CV 106 | 107 | [awesome-hand-pose-estimation](https://github.com/xinghaochen/awesome-hand-pose-estimation): Awesome work on hand pose estimation/tracking 108 | 109 | [CV-Backbones](https://github.com/huawei-noah/CV-Backbones) : CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab. 110 | 111 | [SceneTextPapers](https://github.com/Jyouhou/SceneTextPapers.git): Tracking the latest progress in Scene Text Detection and Recognition: Must-read papers well organized 112 | 113 | [Awesome-GANs](https://github.com/kozistr/Awesome-GANs) : Awesome Generative Adversarial Networks with tensorflow 114 | 115 | [OCR_DataSet](https://github.com/WenmuZhou/OCR_DataSet) : Collect and sort out the data set related to OCR and unify the annotation format for the needs of the experiment 116 | 117 | [awesome-ocr](https://github.com/wanghaisheng/awesome-ocr) : A curated list of promising OCR resources 118 | 119 | [Awesome-Table-Recognition](https://github.com/cv-small-snails/Awesome-Table-Recognition) : A curated list of resources dedicated to table recognition 120 | 121 | [awesome-object-detection](https://github.com/amusi/awesome-object-detection) : Awesome Object Detection based on handong1587 github 122 | 123 | [deep_learning_object_detection](https://github.com/hoya012/deep_learning_object_detection) : A paper list of object detection using deep learning. 124 | 125 | [awesome-captcha](https://github.com/ZYSzys/awesome-captcha) : 🔑 Curated list of awesome captcha libraries and crack tools. 126 | 127 | [image-to-image-papers](https://github.com/lzhbrian/image-to-image-papers) : 🦓<->🦒 🌃<->🌆 A collection of image to image papers with code (constantly updating) 128 | 129 | [Deep-Learning-Papers-Reading-Roadmap](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap) : Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech! 130 | 131 | [benchmark_results](https://github.com/foolwood/benchmark_results) : Visual Tracking Paper List 132 | 133 | [awesome_3DReconstruction_list](https://github.com/openMVG/awesome_3DReconstruction_list) : A curated list of papers & resources linked to 3D reconstruction from images. 134 | 135 | [the-gan-zoo](https://github.com/hindupuravinash/the-gan-zoo) : A list of all named GANs! 136 | 137 | [awesome-computer-vision](https://github.com/jbhuang0604/awesome-computer-vision) : A curated list of awesome computer vision resources 138 | 139 | [multi-object-tracking-paper-list](https://github.com/SpyderXu/multi-object-tracking-paper-list) : Paper list and source code for multi-object-tracking 140 | 141 | [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision) : A curated list of deep learning resources for computer vision 142 | 143 | [AdversarialNetsPapers](https://github.com/zhangqianhui/AdversarialNetsPapers) : Awesome paper list with code about generative adversarial nets (gan) 144 | 145 | [awesome-lane-detection](https://github.com/amusi/awesome-lane-detection) : A paper list of lane detection. 146 | 147 | [Paper_Reading_List](https://github.com/ArcherFMY/Paper_Reading_List) : Recommended Papers. Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI); Learning (cs.LG) 148 | 149 | [awesome-network-embedding](https://github.com/chihming/awesome-network-embedding) : A curated list of network embedding techniques. 150 | 151 | [gans-awesome-applications](https://github.com/nashory/gans-awesome-applications) : Curated list of awesome GAN applications and demo 152 | 153 | [WeakSupervisedSegmentationList](https://github.com/JackieZhangdx/WeakSupervisedSegmentationList) : This repository contains lists of state-or-art weakly supervised semantic segmentation works 154 | 155 | [awesome-action-recognition](https://github.com/jinwchoi/awesome-action-recognition) : A curated list of action recognition and related area resources 156 | 157 | [really-awesome-gan](https://github.com/nightrome/really-awesome-gan) : A list of papers on Generative Adversarial (Neural) Networks 158 | 159 | [awesome-panoptic-segmentation](https://github.com/Angzz/awesome-panoptic-segmentation) : Panoptic Segmentation Resources List 160 | 161 | [Pedestrian-Attribute-Recognition-Paper-List](https://github.com/wangxiao5791509/Pedestrian-Attribute-Recognition-Paper-List) : Paper list on Pedestrian Attribute Recognition (PAR) and related tasks (Pattern Recognition 2021) 162 | 163 | [awesome-vqa](https://github.com/chingyaoc/awesome-vqa) : Visual Q&A reading list 164 | 165 | [3D-Shape-Analysis-Paper-List](https://github.com/yinyunie/3D-Shape-Analysis-Paper-List) : A list of recent papers, libraries and datasets about 3D shape/scene analysis (by topics, updating). 166 | 167 | [awesome-semantic-segmentation](https://github.com/mrgloom/awesome-semantic-segmentation) : awesome-semantic-segmentation 168 | 169 | [Awesome-Crowd-Counting](https://github.com/gjy3035/Awesome-Crowd-Counting) : Awesome Crowd Counting 170 | 171 | [awesome-Face_Recognition](https://github.com/ChanChiChoi/awesome-Face_Recognition) : papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval; 172 | 173 | [AWESOME-FER](https://github.com/EvelynFan/AWESOME-FER) : Top conferences & Journals focused on Facial expression recognition (FER)/ Facial action unit (FAU) 174 | 175 | [Awesome-Gaze-Estimation](https://github.com/cvlab-uob/Awesome-Gaze-Estimation) : Awesome Curated List of Eye Gaze Estimation Paper 176 | 177 | [awesome-ai-art-image-synthesis](https://github.com/altryne/awesome-ai-art-image-synthesis) : A list of awesome tools, ideas, prompt engineering tools, colabs, models, and helpers for the prompt designer playing with aiArt and image synthesis. Covers Dalle2, MidJourney, StableDiffusion, and open source tools. 178 | 179 | [Diffusion-Models-Papers-Survey-Taxonomy](https://github.com/YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy) : Diffusion model papers, survey, and taxonomy 180 | 181 | [A-Survey-on-Generative-Diffusion-Model](https://github.com/chq1155/A-Survey-on-Generative-Diffusion-Model) : A curated list for diffusion generative models introduced by the paper 182 | 183 | [Awesome-Face-Restoration](https://github.com/TaoWangzj/Awesome-Face-Restoration) : A comprehensive list of recources (papers, repositories etc.) about face restoration methods. 184 | 185 | [awesome-point-cloud-analysis](https://github.com/Yochengliu/awesome-point-cloud-analysis) : A list of papers and datasets about point cloud analysis (processing) 186 | 187 | [awesome-ai-painting](https://github.com/hua1995116/awesome-ai-painting) : stable diffusion tutorial、disco diffusion tutorial、 AI Platform 188 | 189 | [awesome-aigc](https://github.com/gongminmin/awesome-aigc) : A list of awesome AIGC works 190 | 191 | [awesome-llm-and-aigc](https://github.com/codingonion/awesome-llm-and-aigc) : A collection of some awesome public projects about Large Language Model, Vision Foundation Model and AI Generated Content. 192 | 193 | [awesome-text-to-video](https://github.com/jianzhnie/awesome-text-to-video) : A Survey on Text-to-Video Generation/Synthesis. 194 | 195 | [Awesome-AIGC-Tutorials](https://github.com/luban-agi/Awesome-AIGC-Tutorials) : Curated tutorials and resources for Large Language Models, AI Painting, and more. 196 | 197 | [Awesome-AIGC](https://github.com/wshzd/Awesome-AIGC) : AIGC资料汇总学习，持续更新...... 198 | 199 | 200 | 201 | ## NLP 202 | 203 | 204 | 205 | [nlp-tutorial](https://github.com/graykode/nlp-tutorial) : Natural Language Processing Tutorial for Deep Learning Researchers 206 | 207 | [language-resources](https://github.com/google/language-resources) : Datasets and tools for basic natural language processing. 208 | 209 | [Summarization-Papers](https://github.com/xcfcode/Summarization-Papers) ： Summarization Papers 210 | 211 | [CLUEDatasetSearch](https://github.com/CLUEbenchmark/CLUEDatasetSearch) ： Search all Chinese NLP datasets, with common English NLP datasets 212 | 213 | [nlpdemo-ch-wordlib](https://github.com/MrLi008/nlpdemo-ch-wordlib) : Chinese Thesaurus 214 | 215 | [ChineseNLP](https://github.com/didi/ChineseNLP) : Datasets, SOTA results of every fields of Chinese NLP 216 | 217 | [ChineseNLPCorpus](https://github.com/InsaneLife/ChineseNLPCorpus) : Chinese natural language processing data set is the material for experiments at ordinary times. 中文自然语言处理数据集 218 | 219 | [Chinese-Word-Vectors](https://github.com/Embedding/Chinese-Word-Vectors) : 100+ Chinese Word Vectors 上百种预训练中文词向量 220 | 221 | [ChineseNlpCorpus](https://github.com/SophonPlus/ChineseNlpCorpus) : Collect, organize and publish Chinese natural language processing corpus / data set 222 | 223 | [nlp-competitions-list-review](https://github.com/zhpmatrix/nlp-competitions-list-review) : Resume the top plan of all NLP competitions, only focus on NLP competitions, and keep updating! NLP比赛top方案 224 | 225 | [funNLP](https://github.com/fighting41love/funNLP) : Chinese and English sensitive words, language detection, Chinese and foreign mobile phone / telephone home / operator query, name inference, gender, mobile phone number extraction, ID card extraction, email extraction, and more ... 有趣的中文NLP 226 | 227 | [nlp_chinese_corpus](https://github.com/brightmart/nlp_chinese_corpus) : 大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP 228 | 229 | [awesome-2vec](https://github.com/MaxwellRebo/awesome-2vec) : Curated list of 2vec-type embedding models 230 | 231 | [chatbot-list](https://github.com/lizhe2004/chatbot-list) : Share and introduce the application, architecture and algorithm of intelligent customer service and chat robot in the industry 行业内关于智能客服、聊天机器人的应用和架构、算法分享和介绍 232 | 233 | [awesome-chatbot-list](https://github.com/aceimnorstuvwxz/awesome-chatbot-list) : 深度学习聊天机器人资源集合 Awesome chatbot resource list 234 | 235 | [nmt-list](https://github.com/jonsafari/nmt-list) : A list of Neural MT implementations 236 | 237 | [Question-Generation-Paper-List](https://github.com/teacherpeterpan/Question-Generation-Paper-List) : A summary of must-read papers for Neural Question Generation (NQG) 238 | 239 | [awesome-nlp](https://github.com/keon/awesome-nlp) : 📖 A curated list of resources dedicated to Natural Language Processing (NLP) 240 | 241 | [Style-Transfer-in-Text](https://github.com/fuzhenxin/Style-Transfer-in-Text) : Paper List for Style Transfer in Text 242 | 243 | [TG-Reading-List](https://github.com/THUNLP-MT/TG-Reading-List) : A text generation reading list maintained by Tsinghua Natural Language Processing Group. 244 | 245 | [awesome-sentence-embedding](https://github.com/Separius/awesome-sentence-embedding) : A curated list of pretrained sentence and word embedding models 246 | 247 | [Awesome-Chinese-NLP](https://github.com/crownpku/Awesome-Chinese-NLP) : A curated list of resources for Chinese NLP 中文自然语言处理相关资料 248 | 249 | [*awesome*_Chinese_medical_*NLP*](https://github.com/GanjinZero/awesome_Chinese_medical_NLP) : Arrangement of Chinese medical NLP public resources 中文医学NLP公开资源整理：术语集/语料库/词向量/预训练模型/知识图谱/命名实体识别/QA/信息抽取/模型/论文/etc 250 | 251 | [awesome-dl4nlp](https://github.com/brianspiering/awesome-dl4nlp) : A curated list of awesome Deep Learning for Natural Language Processing resources 252 | 253 | [Awesome-Korean-NLP](https://github.com/datanada/Awesome-Korean-NLP) : A curated list of resources for NLP (Natural Language Processing) for Korean 254 | 255 | [awesome-bert-nlp](https://github.com/cedrickchee/awesome-bert-nlp) : A curated list of NLP resources focused on BERT, attention mechanism, Transformer networks, and transfer learning. 256 | 257 | [awesome-knowledge-graph](https://github.com/husthuke/awesome-knowledge-graph) : a cute list of Knowledge graph 258 | 259 | [Task-Oriented-Dialogue-Research-Progress-Survey](https://github.com/AtmaHou/Task-Oriented-Dialogue-Research-Progress-Survey) : A datasets and methods survey about task-oriented dialogue, including recent datasets and SOTA leaderboards. 260 | 261 | [Text_Classification](https://github.com/kk7nc/Text_Classification) : Text Classification Algorithms: A Survey 262 | 263 | [awesome-punctuator](https://github.com/bigcash/awesome-punctuator) : A curated list of awesome punctuator 264 | 265 | [text-classification-surveys](https://github.com/xiaoqian19940510/text-classification-surveys) : 文本分类资源汇总，包括深度学习文本分类模型 266 | 267 | [awesome_Chinese_medical_NLP](https://github.com/GanjinZero/awesome_Chinese_medical_NLP) : 中文医学NLP公开资源整理：术语集/语料库/词向量/预训练模型/知识图谱/命名实体识别/QA/信息抽取/模型/论文/etc 268 | 269 | [Awesome-LLM](https://github.com/Hannibal046/Awesome-LLM) : Awesome-LLM: a curated list of Large Language Model 270 | 271 | [Prompt-Engineering-Guide](https://github.com/dair-ai/Prompt-Engineering-Guide) : Guides, papers, lecture, and resources for prompt engineering 272 | 273 | [PromptPapers](https://github.com/thunlp/PromptPapers) : Must-read papers on prompt-based tuning for pre-trained language models. 274 | 275 | [awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts) : This repo includes ChatGPT prompt curation to use ChatGPT better. 276 | 277 | [awesome-chatgpt-prompts-zh](https://github.com/PlexPt/awesome-chatgpt-prompts-zh) : ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。 278 | 279 | [awesome-gpt3](https://github.com/elyase/awesome-gpt3) : Awesome GPT-3 is a collection of demos and articles about the [OpenAI GPT-3 API](https://openai.com/blog/openai-api/). 280 | 281 | [Awesome-ChatGPT](https://github.com/dalinvip/Awesome-ChatGPT) : ChatGPT资料汇总学习，持续更新...... 282 | 283 | [awesome-open-gpt](https://github.com/EwingYangs/awesome-open-gpt) : Collection of Open Source Projects Related to GPT，GPT相关开源项目合集🚀、精选🔥🔥 284 | 285 | [awesome-chatgpt](https://github.com/humanloop/awesome-chatgpt) : Curated list of awesome tools, demos, docs for ChatGPT and GPT-3 286 | 287 | [awesome-gpt4](https://github.com/radi-cho/awesome-gpt4) : A curated list of prompts, tools, and resources regarding the GPT-4 language model. 288 | 289 | [Awesome-ChatGPT](https://github.com/runningcheese/Awesome-ChatGPT) : ChatGPT related knowledge and resource 290 | 291 | [awesome-gpt](https://github.com/formulahendry/awesome-gpt) : A curated list of awesome projects and resources related to GPT, ChatGPT, OpenAI, LLM, and more. 292 | 293 | [awesome-instruction-dataset](https://github.com/yaodongC/awesome-instruction-dataset) : A collection of open-source dataset to train instruction-following LLMs (ChatGPT,LLaMA,Alpaca) 294 | 295 | [LLMSurvey](https://github.com/RUCAIBox/LLMSurvey) : The official GitHub page for the survey paper "A Survey of Large Language Models". 296 | 297 | [awesome-langchain](https://github.com/kyrolabs/awesome-langchain) : Awesome list of tools and projects with the awesome LangChain framework 298 | [awesome-pretrained-chinese-nlp-models](https://github.com/lonePatient/awesome-pretrained-chinese-nlp-models) : Awesome Pretrained Chinese NLP Models 299 | 300 | [Awesome-Multimodal-Large-Language-Models](https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models) : Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation. 301 | 302 | [awesome-LLMs-In-China](https://github.com/wgwang/awesome-LLMs-In-China) : LLMs in china 303 | 304 | [awesome-open-foundation-models](https://github.com/wgwang/awesome-open-foundation-models) : Open foundation models, such LLama2, ChatGLM, etc. 305 | 306 | [awesome-LLM-benchmarks](https://github.com/wgwang/awesome-LLM-benchmarks) : Awesome LLM Benchmarks to evaluate the LLMs across text, code, image, audio, video and more. 307 | 308 | [Awesome-Chinese-LLM](https://github.com/HqWu-HITCS/Awesome-Chinese-LLM) : 整理开源的中文大语言模型，以规模较小、可私有化部署、训练成本较低的模型为主，包括底座模型，垂直领域微调及应用，数据集与教程等。 309 | 310 | [Awesome-Domain-LLM](https://github.com/luban-agi/Awesome-Domain-LLM) : 收集和梳理垂直领域的开源模型、数据集及评测基准。 311 | 312 | [DecryptPrompt](https://github.com/DSXiangLi/DecryptPrompt) : 总结Prompt&LLM论文，开源数据&模型，AIGC应用 313 | 314 | [Awesome-Open-domain-Dialogue-Models](https://github.com/cingtiye/Awesome-Open-domain-Dialogue-Models) : Awesome Open-domain Dialogue Models，高质量开放域对话模型集合 315 | 316 | [LLMDataHub](https://github.com/Zjh-819/LLMDataHub) : A quick guide (especially) for trending instruction finetuning datasets 317 | 318 | [NLPer-Arsenal](https://github.com/TingFree/NLPer-Arsenal) : 收录NLP竞赛策略实现、各任务baseline、相关竞赛经验贴（当前赛事、往期赛事、训练赛）、NLP会议时间、常用自媒体、GPU推荐等 319 | 320 | [awesome-llm-apps](https://github.com/Shubhamsaboo/awesome-llm-apps) : Collection of awesome LLM apps with RAG using OpenAI, Anthropic, Gemini and opensource models. 321 | 322 | [llm-app](https://github.com/pathwaycom/llm-app) : Dynamic RAG for enterprise. Ready to run with Docker,⚡in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more. 323 | 324 | [Awesome-LLM-RAG-Application](https://github.com/lizhe2004/Awesome-LLM-RAG-Application) : the resources about the application based on LLM with RAG pattern 325 | 326 | [Awesome-Text2SQL](https://github.com/eosphoros-ai/Awesome-Text2SQL) : Curated tutorials and resources for Large Language Models, Text2SQL, Text2DSL、Text2API、Text2Vis and more. 327 | 328 | [NL2SQL](https://github.com/yechens/NL2SQL) : Text2SQL 语义解析数据集、解决方案、paper资源整合项目 329 | 330 | [awesome-chatgpt-dataset](https://github.com/voidful/awesome-chatgpt-dataset) : Unlock the Power of LLM: Explore These Datasets to Train Your Own ChatGPT! 331 | 332 | [Awesome-LLM-Reasoning](https://github.com/atfortes/Awesome-LLM-Reasoning) : Reasoning in Large Language Models: Papers and Resources, including Chain-of-Thought and OpenAI o1 🍓 333 | 334 | [Awesome-LLM-Strawberry](https://github.com/hijkzzz/Awesome-LLM-Strawberry) : A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 and reasoning techniques. 335 | 336 | [Awesome-LLMOps](https://github.com/tensorchord/Awesome-LLMOps) : An awesome & curated list of best LLMOps tools for developers 337 | 338 | [awesome-LLM-resourses](https://github.com/WangRongsheng/awesome-LLM-resourses) : 🧑‍🚀 全世界最好的LLM资料总结 | Summary of the world's best LLM resources. 339 | 340 | [Awesome-LLM-Robotics](https://github.com/GT-RIPL/Awesome-LLM-Robotics) : A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites 341 | 342 | [Awesome-LLM-Inference](https://github.com/DefTruth/Awesome-LLM-Inference) : 📖A curated list of Awesome LLM Inference Paper with codes, TensorRT-LLM, vLLM, streaming-llm, AWQ, SmoothQuant, WINT8/4, Continuous Batching, FlashAttention, PagedAttention etc. 343 | 344 | [Awesome-LLM-RAG](https://github.com/jxzhangjhu/Awesome-LLM-RAG) : Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models 345 | 346 | [Awesome-LLM-Compression](https://github.com/HuangOwen/Awesome-LLM-Compression) : Awesome LLM compression research papers and tools. 347 | 348 | [Awesome-LLMs-on-device](https://github.com/NexaAI/Awesome-LLMs-on-device) : Awesome LLMs on Device: A Comprehensive Survey 349 | 350 | [Awesome-LLMs-Datasets](https://github.com/lmmlzn/Awesome-LLMs-Datasets) : Summarize existing representative LLMs text datasets. 351 | 352 | [awesome-ml](https://github.com/underlines/awesome-ml) : Curated list of useful LLM / Analytics / Datascience resources 353 | 354 | [awesome-llm-security](https://github.com/corca-ai/awesome-llm-security) : A curation of awesome tools, documents and projects about LLM Security. 355 | 356 | [Awesome-LLM4AD](https://github.com/Thinklab-SJTU/Awesome-LLM4AD) : A curated list of awesome LLM for Autonomous Driving resources 357 | 358 | [awesome-llm-powered-agent](https://github.com/hyp1231/awesome-llm-powered-agent) : Awesome things about LLM-powered agents. Papers / Repos / Blogs 359 | 360 | [awesome-llm-json](https://github.com/imaurer/awesome-llm-json) : Resource list for generating JSON using LLMs via function calling, tools, CFG. Libraries, Models, Notebooks, etc. 361 | 362 | [Awesome-Code-LLM](https://github.com/codefuse-ai/Awesome-Code-LLM) : A curated list of language modeling researches for code and related datasets. 363 | 364 | [awesome-llm-interpretability](https://github.com/JShollaj/awesome-llm-interpretability) : A curated list of Large Language Model (LLM) Interpretability resources. 365 | 366 | [Awesome-Graph-LLM](https://github.com/XiaoxinHe/Awesome-Graph-LLM) : A collection of AWESOME things about Graph-Related LLMs. 367 | 368 | [Awesome-GPT-Agents](https://github.com/fr0gger/Awesome-GPT-Agents) : A curated list of GPT agents for cybersecurity 369 | 370 | [LLM4Rec-Awesome-Papers](https://github.com/WLiK/LLM4Rec-Awesome-Papers) : A list of awesome papers and resources of recommender system on large language model (LLM). 371 | 372 | [Awesome-LLM-KG](https://github.com/RManLuo/Awesome-LLM-KG) : Awesome papers about unifying LLMs and KGs 373 | 374 | [awesome_LLMs_interview_notes](https://github.com/jackaduma/awesome_LLMs_interview_notes) : LLMs interview notes and answers:该仓库主要记录大模型（LLMs）算法工程师相关的面试题和参考答案 375 | 376 | 377 | 378 | ## Speech 379 | 380 | [awesome-speech-recognition-speech-synthesis-papers](https://github.com/zzw922cn/awesome-speech-recognition-speech-synthesis-papers) ： Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC) 381 | 382 | [Speech-Separation-Paper-Tutorial](https://github.com/JusperLee/Speech-Separation-Paper-Tutorial) ： A must-read paper for speech separation based on neural networks 383 | 384 | [speech-recognition-papers](https://github.com/wenet-e2e/speech-recognition-papers): Towards hot directions in industrial end to end speech recognition 385 | 386 | [awesome-data-augmentation](https://github.com/CrazyVertigo/awesome-data-augmentation)![](https://img.shields.io/github/stars/CrazyVertigo/awesome-data-augmentation.svg?style=social)： This is a list of awesome methods about data augmentation. 387 | 388 | [Awesome-SLP](https://github.com/BenSaunders27/Awesome-SLP.git): A curated list of awesome work on Sign Language Production 389 | 390 | [Awesome-SLU-Survey](https://github.com/yizhen20133868/Awesome-SLU-Survey) ： Tracking the progress in SLU (resources, code, and new frontiers etc.) 391 | 392 | [speech_dataset](https://github.com/double22a/speech_dataset): The dataset of Speech Recognition 393 | 394 | [awesome_OpenSetRecognition_list](https://github.com/iCGY96/awesome_OpenSetRecognition_list): A curated list of papers & resources linked to open set recognition, out-of-distribution, open set domain adaptation and open world recognition 395 | 396 | [speech-synthesis-paper](https://github.com/wenet-e2e/speech-synthesis-paper) : List of speech synthesis papers. 397 | 398 | [Awesome-Speech-Enhancement](https://github.com/nanahou/Awesome-Speech-Enhancement) ： A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful. 399 | 400 | [awesome-speech-enhancement](https://github.com/WenzheLiu-Speech/awesome-speech-enhancement) : speech enhancement\speech seperation\sound source localization 401 | 402 | [speech_data_augment](https://github.com/zzpDapeng/speech_data_augment) : A summary of speech data augment algorithms 403 | 404 | [wer_are_we](https://github.com/syhw/wer_are_we) : Attempt at tracking states of the arts and recent results (bibliography) on speech recognition. 405 | 406 | [awesome-diarization](https://github.com/wq2012/awesome-diarization) : A curated list of awesome Speaker Diarization papers, libraries, datasets, and other resources. 407 | 408 | [awesome-audio-visualization](https://github.com/willianjusten/awesome-audio-visualization) : A curated list about Audio Visualization. 409 | 410 | [awesome-deep-learning-music](https://github.com/ybayle/awesome-deep-learning-music) : List of articles related to deep learning applied to music 411 | 412 | [speech-language-processing](https://github.com/edobashira/speech-language-processing) : A curated list of speech and natural language processing resources 413 | 414 | [SpeechAlgorithms](https://github.com/Ryuk17/SpeechAlgorithms) : Speech Algorithms Collections 415 | 416 | [awesome-vad](https://github.com/bigcash/awesome-vad) : A curated list of awesome voice activity detection 417 | 418 | [SER-datasets](https://github.com/SuperKogito/SER-datasets) : A collection of datasets for the purpose of emotion recognition/detection in speech. 419 | 420 | [awesome-openai-whisper](https://github.com/ancs21/awesome-openai-whisper) : A curated list of awesome OpenAI's Whisper 421 | 422 | [Tutorial_Separation](https://github.com/gemengtju/Tutorial_Separation) : This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests. 423 | 424 | [open-speech-corpora](https://github.com/coqui-ai/open-speech-corpora) : 💎 A list of accessible speech corpora for ASR, TTS, and other Speech Technologies 425 | 426 | [awesome-vits](https://github.com/34j/awesome-vits) : List of repositories relevant to VITS. 427 | 428 | [Awesome-Text-to-Speech-TTS](https://github.com/TouchSky-Lab/Awesome-Text-to-Speech-TTS) : Awesome TTS 429 | 430 | [awesome-tts-samples](https://github.com/seungwonpark/awesome-tts-samples) : Awesome list of TTS papers with audio samples 431 | 432 | [awesome-disfluency-detection](https://github.com/pariajm/awesome-disfluency-detection) : A curated list of awesome disfluency detection publications along with the released code and bibliographical information 433 | 434 | [WeDataset](https://github.com/wenet-e2e/wenet/issues/2094): List of (OpenSource data) + (Crawler Resources) 435 | 436 | 437 | 438 | ## Others 439 | 440 | [anomaly-detection-resources](https://github.com/yzhao062/anomaly-detection-resources) : Anomaly detection related books, papers, videos, and toolboxes 441 | 442 | [awesome-anomaly-detection](https://github.com/hoya012/awesome-anomaly-detection) : A curated list of awesome anomaly detection resources 443 | 444 | [Surface-Defect-Detection](https://github.com/Charmve/Surface-Defect-Detection) : Constantly summarizing open source dataset and critical papers in the field of surface defect research which are of great importance. 445 | 446 | [Awesome-Meta-Learning](https://github.com/sudharsan13296/Awesome-Meta-Learning) : A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources. 447 | 448 | [GitHub-Chinese-Top-Charts](https://github.com/GrowingGit/GitHub-Chinese-Top-Charts) : 🇨🇳 GitHub chinese top list 中文排行榜，各语言分离设置「软件 / 资料」榜单，精准定位中文好项目。各取所需，互不干扰，高效学习。 449 | 450 | [state-of-the-art-result-for-machine-learning-problems](https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems) : This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). 451 | 452 | [PyTorchTricks](https://github.com/lartpang/PyTorchTricks) : Some tricks of pytorch... ⭐ 453 | 454 | [Awesome-pytorch-list-CNVersion](https://github.com/xavier-zy/Awesome-pytorch-list-CNVersion) : Awesome-pytorch-list 翻译工作进行中...... 455 | 456 | [Awesome-pytorch-list](https://github.com/bharathgs/Awesome-pytorch-list) : A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc. 457 | 458 | [deeplearning-models](https://github.com/rasbt/deeplearning-models) : A collection of various deep learning architectures, models, and tips 459 | 460 | [awesome-data-labeling](https://github.com/heartexlabs/awesome-data-labeling) : A curated list of awesome data labeling tools 461 | 462 | [Awesome-Learning-with-Label-Noise](https://github.com/subeeshvasu/Awesome-Learning-with-Label-Noise) : A curated list of resources for Learning with Noisy Labels 463 | 464 | [awesome-music-production](https://github.com/ad-si/awesome-music-production.git): A curated list of software, services and resources to create and distribute music. 465 | 466 | [leetcode-master](https://github.com/youngyangyang04/leetcode-master) ： LeetCode Introduction 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀 467 | 468 | [awesome-python-login-model](https://github.com/Kr1s77/awesome-python-login-model) ： 😮python crawlers 模拟登陆一些大型网站，还有一些简单的爬虫， 469 | 470 | [awesome-spider](https://github.com/facert/awesome-spider) : crawlers list 爬虫集合 471 | 472 | [awesome-python](https://github.com/vinta/awesome-python) : A curated list of awesome Python frameworks, libraries, software and resources 473 | 474 | [awesome-remote-job](https://github.com/lukasz-madon/awesome-remote-job) : A curated list of awesome remote jobs and resources. 475 | 476 | [public-apis](https://github.com/public-apis/public-apis) : A collective list of free APIs 477 | 478 | [Public-APIs](https://github.com/n0shake/Public-APIs) : 📚 A public list of APIs from round the web. 479 | 480 | [public-api-lists](https://github.com/public-api-lists/public-api-lists) : A collective list of free APIs for use in software and web development 🚀 481 | 482 | [lists](https://github.com/jnv/lists) : The definitive list of lists (of lists) curated on GitHub and elsewhere 483 | 484 | [interview](https://github.com/Olshansk/interview) : Everything you need to prepare for your technical interview 485 | 486 | [A-to-Z-Resources-for-Students](https://github.com/dipakkr/A-to-Z-Resources-for-Students) : ✅ Curated list of resources for college students 487 | 488 | [awesome-math](https://github.com/rossant/awesome-math) : A curated list of awesome mathematics resources 489 | 490 | [awesome-raspberry-pi](https://github.com/thibmaek/awesome-raspberry-pi) : 📝 A curated list of awesome Raspberry Pi tools, projects, images and resources 491 | 492 | [science-based-games-list](https://github.com/stared/science-based-games-list) : Science-based games - a collaborative list 493 | 494 | [awesome-SLAM-list](https://github.com/OpenSLAM/awesome-SLAM-list) : awesome-SLAM-list 495 | 496 | [awesome-slam](https://github.com/kanster/awesome-slam) : A curated list of awesome SLAM tutorials, projects and communities. 497 | 498 | [SLAM-All-In-One](https://github.com/zhouyong1234/SLAM-All-In-One) : SLAM汇总，包括多传感器融合建图、定位、VIO系列、常用工具包、开源代码注释和公式推导、文章综述 499 | 500 | [awesome-robotics](https://github.com/kiloreux/awesome-robotics) : A list of awesome Robotics resources 501 | 502 | [TopDeepLearning](https://github.com/aymericdamien/TopDeepLearning) : A list of popular github projects related to deep learning 503 | 504 | [awesome-ai-residency](https://github.com/dangkhoasdc/awesome-ai-residency) : List of AI Residency Programs 505 | 506 | [ICRA2020-paper-list](https://github.com/PaoPaoRobot/ICRA2020-paper-list) : ICRA2020 paperlist by paopaorobot, ICRA 2020 : the 2020 IEEE International Conference on Robotics and Automation. 507 | 508 | [RSPapers](https://github.com/hongleizhang/RSPapers) : A Curated List of Must-read Papers on Recommender System. 509 | 510 | [Awesome-Embedded](https://github.com/nhivp/Awesome-Embedded) : A curated list of awesome embedded programming. 511 | 512 | [useful-computer-vision-phd-resources](https://github.com/hassony2/useful-computer-vision-phd-resources) : Lists of resources useful for my PhD in computer vision 513 | 514 | [spatio-temporal-paper-list](https://github.com/Eilene/spatio-temporal-paper-list) : Spatio-temporal modeling 论文列表（主要是graph convolution相关) 515 | 516 | [awesome-self-supervised-learning](https://github.com/jason718/awesome-self-supervised-learning) : A curated list of awesome self-supervised methods 517 | 518 | [medical-imaging-datasets](https://github.com/sfikas/medical-imaging-datasets) : A list of Medical imaging datasets. 519 | 520 | [awesome-roadmaps](https://github.com/liuchong/awesome-roadmaps) : A curated list of roadmaps. 521 | 522 | [EEG-Datasets](https://github.com/meagmohit/EEG-Datasets) : A list of all public EEG-datasets 523 | 524 | [MARL-Papers](https://github.com/LantaoYu/MARL-Papers) : Paper list of multi-agent reinforcement learning (MARL) 525 | 526 | [awesome-multimodal-ml](https://github.com/pliang279/awesome-multimodal-ml) : Reading list for research topics in multimodal machine learning 527 | 528 | [Awesome-Multimodal-Research](https://github.com/Eurus-Holmes/Awesome-Multimodal-Research) : A curated list of Multimodal Related Research. 529 | 530 | [deep-reinforcement-learning-papers](https://github.com/junhyukoh/deep-reinforcement-learning-papers) : A list of recent papers regarding deep reinforcement learning 531 | 532 | [awesome-machine-learning-interpretability](https://github.com/jphall663/awesome-machine-learning-interpretability) : A curated list of awesome machine learning interpretability resources. 533 | 534 | [awesome-fast-attention](https://github.com/Separius/awesome-fast-attention) : list of efficient attention modules 535 | 536 | [deeplearning-biology](https://github.com/hussius/deeplearning-biology) : A list of deep learning implementations in biology 537 | 538 | [FreeML](https://github.com/Shujian2015/FreeML) : A List of Data Science/Machine Learning Resources (Mostly Free) 539 | 540 | [Paper-List](https://github.com/ConanCui/Paper-List) : A reading paper list which is mainted daily 541 | 542 | [awesome-jupyter](https://github.com/markusschanta/awesome-jupyter) : A curated list of awesome Jupyter projects, libraries and resources 543 | 544 | [the-incredible-pytorch](https://github.com/ritchieng/the-incredible-pytorch) : The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch. 545 | 546 | [awesome-quant](https://github.com/wilsonfreitas/awesome-quant) : A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance) 547 | 548 | [awesome-quant](https://github.com/thuquant/awesome-quant) : quant related resources index in China 549 | 550 | [awesome-community-detection](https://github.com/benedekrozemberczki/awesome-community-detection) : A curated list of community detection research papers with implementations. 551 | 552 | [awesome-robotics-libraries](https://github.com/jslee02/awesome-robotics-libraries) : 😎 A curated list of robotics libraries and software 553 | 554 | [awesome_time_series_in_python](https://github.com/MaxBenChrist/awesome_time_series_in_python) : This curated list contains python packages for time series analysis 555 | 556 | [awesome-rnn](https://github.com/kjw0612/awesome-rnn) : Recurrent Neural Network - A curated list of resources dedicated to RNN 557 | 558 | [awesome-random-forest](https://github.com/kjw0612/awesome-random-forest) : Random Forest - a curated list of resources regarding random forest 559 | 560 | [awesome-adversarial-machine-learning](https://github.com/yenchenlin/awesome-adversarial-machine-learning) : A curated list of awesome adversarial machine learning resources 561 | 562 | [awesome-awesome](https://github.com/emijrp/awesome-awesome) : A curated list of awesome curated lists of many topics. 563 | 564 | [VR-Awesome](https://github.com/Vytek/VR-Awesome) : VR Awesome List 565 | 566 | [machine-learning-surveys](https://github.com/metrofun/machine-learning-surveys) : A curated list of Machine Learning Surveys, Tutorials and Books. 567 | 568 | [awesome-rl](https://github.com/aikorea/awesome-rl) : Reinforcement learning resources curated 569 | 570 | [awesome-knowledge-distillation](https://github.com/dkozlov/awesome-knowledge-distillation) : Awesome Knowledge Distillation 571 | 572 | [Awesome-Incremental-Learning](https://github.com/xialeiliu/Awesome-Incremental-Learning) : Awesome Incremental Learning 573 | 574 | [awesome-graph-classification](https://github.com/benedekrozemberczki/awesome-graph-classification) : A collection of important graph embedding, classification and representation learning papers with implementations. 575 | 576 | [Awesome-Transformer-Attention](https://github.com/cmhungsteve/Awesome-Transformer-Attention) ： An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites 577 | 578 | [awesome-public-datasets](https://github.com/awesomedata/awesome-public-datasets) : A topic-centric list of HQ open datasets. 579 | 580 | [awesome-ai-in-finance](https://github.com/georgezouq/awesome-ai-in-finance) : 🔬 A curated list of awesome machine learning strategies & tools in financial market. 581 | 582 | [Awesome-explainable-AI](https://github.com/wangyongjie-ntu/Awesome-explainable-AI) : A collection of research materials on explainable AI/ML 583 | 584 | [Awesome-Federated-Learning](https://github.com/chaoyanghe/Awesome-Federated-Learning) : FedML - The Research and Production Integrated Federated Learning Library 585 | 586 | [Awesome-AI-Security](https://github.com/DeepSpaceHarbor/Awesome-AI-Security) : A curated list of AI security resources inspired by [awesome-adversarial-machine-learning](https://github.com/yenchenlin/awesome-adversarial-machine-learning) & [awesome-ml-for-cybersecurity](https://github.com/jivoi/awesome-ml-for-cybersecurity). 587 | 588 | [awesome-deep-rl](https://github.com/tigerneil/awesome-deep-rl) : For deep RL and the future of AI. 589 | 590 | [awesome-fashion-ai](https://github.com/ayushidalmia/awesome-fashion-ai) : A repository to curate and summarise research papers related to fashion and e-commerce 591 | 592 | [awesome-blockchain-ai](https://github.com/steven2358/awesome-blockchain-ai) : A curated list of Blockchain projects for Artificial Intelligence and Machine Learning 593 | 594 | [awesome-starcraftAI](https://github.com/SKTBrain/awesome-starcraftAI) : A curated list of resources dedicated to StarCraft AI. 595 | 596 | [awesome-game-ai](https://github.com/datamllab/awesome-game-ai) : Awesome Game AI materials of Multi-Agent Reinforcement Learning 597 | 598 | [awesome-feature-engineering](https://github.com/aikho/awesome-feature-engineering) : A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning 599 | 600 | [awesome-ai-usecases](https://github.com/JosPolfliet/awesome-ai-usecases) : A list of awesome and proven Artificial Intelligence use cases and applications 601 | 602 | [lite.ai.toolkit](https://github.com/DefTruth/lite.ai.toolkit) : A lite C++ toolkit of awesome AI models with ONNXRuntime, NCNN, MNN and TNN. YOLOX, YOLOP, YOLOv6, YOLOR, MODNet, YOLOX, YOLOv7, YOLOv5. MNN, NCNN, TNN, ONNXRuntime. 603 | 604 | [awesome-ai](https://github.com/hades217/awesome-ai) : A curated list of artificial intelligence resources (Courses, Tools, App, Open Source Project) 605 | 606 | [500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code](https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code) : 500 AI Machine learning Deep learning Computer vision NLP Projects with code 607 | 608 | [knowledge-distillation-papers](https://github.com/lhyfst/knowledge-distillation-papers) : knowledge distillation papers 609 | 610 | [Awesome_Continual-Lifelong-Incremental_learning](https://github.com/chengsilin/Awesome_Continual-Lifelong-Incremental_learning) : Awesome Continual-Lifelong-Incremental learning 611 | 612 | [Awesome-Few-Shot-Class-Incremental-Learning](https://github.com/zhoudw-zdw/Awesome-Few-Shot-Class-Incremental-Learning) : Awesome Few-Shot Class Incremental Learning 613 | 614 | [awesome-gcn](https://github.com/Jiakui/awesome-gcn) : resources for graph convolutional networks 615 | 616 | [Awesome-Deep-Graph-Clustering](https://github.com/yueliu1999/Awesome-Deep-Graph-Clustering) : Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets). 617 | 618 | [awesome-denovo-papers](https://github.com/asarigun/awesome-denovo-papers) : Awesome De novo drugs design papers 619 | 620 | [awesome-lidar](https://github.com/szenergy/awesome-lidar) : Awesome LIDAR list. The list includes LIDAR manufacturers, datasets, point cloud-processing algorithms, point cloud frameworks and simulators. 621 | 622 | [awesome-self-supervised-gnn](https://github.com/ChandlerBang/awesome-self-supervised-gnn) : Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN). 623 | 624 | [ai-collection](https://github.com/ai-collection/ai-collection) : The Generative AI Landscape - A Collection of Awesome Generative AI Applications 625 | 626 | [papers-we-love](https://github.com/papers-we-love/papers-we-love) : Papers from the computer science community to read and discuss. 627 | 628 | [Awesome-Autonomous-Driving](https://github.com/autodriving-heart/Awesome-Autonomous-Driving) : awesome-autonomous-driving 629 | 630 | --------------------------------------------------------------------------------