155 lines
25 KiB
Markdown
155 lines
25 KiB
Markdown
<a href="https://github.com/GrowingGit/GitHub-Chinese-Top-Charts#github中文排行榜">返回目录</a> • <a href="/content/docs/feedback.md">问题反馈</a>
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# 中文增速榜 > 资料类 > Jupyter Notebook
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<sub>数据更新: 2022-12-09 / 温馨提示：中文项目泛指「文档母语为中文」OR「含有中文翻译」的项目，通常在项目的「readme/wiki/官网」可以找到</sub>
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|#|Repository|Description|Stars|Average daily growth|Updated|
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|1|[fastai/fastbook](https://github.com/fastai/fastbook)|The fastai book, published as Jupyter Notebooks|16580|16|2022-12-06|
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|2|[Baiyuetribe/paper2gui](https://github.com/Baiyuetribe/paper2gui)|Convert AI papers to GUI，Make it easy and convenient for everyone to use artificial intelligence technology。让每个人都简单方便的使用前沿人工智能技术|6575|15|2022-11-27|
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|3|[fengdu78/lihang-code](https://github.com/fengdu78/lihang-code)|《统计学习方法》的代码实现|16311|11|2022-09-11|
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|4|[NLP-LOVE/ML-NLP](https://github.com/NLP-LOVE/ML-NLP)|此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。|12970|10|2022-06-21|
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|5|[selfteaching/the-craft-of-selfteaching](https://github.com/selfteaching/the-craft-of-selfteaching)|One has no future if one couldn't teach themself.|13640|10|2022-11-01|
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|6|[leandromoreira/digital_video_introduction](https://github.com/leandromoreira/digital_video_introduction)|A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding).|13206|6|2022-10-11|
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|7|[datawhalechina/easy-rl](https://github.com/datawhalechina/easy-rl)|强化学习中文教程（蘑菇书），在线阅读地址：https://datawhalechina.github.io/easy-rl/|5645|6|2022-12-06|
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|8|[chenyuntc/pytorch-book](https://github.com/chenyuntc/pytorch-book)|PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)|10523|5|2022-12-04|
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|9|[wesm/pydata-book](https://github.com/wesm/pydata-book)|Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media|18476|5|2022-11-23|
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|10|[Fafa-DL/Lhy_Machine_Learning](https://github.com/Fafa-DL/Lhy_Machine_Learning)|李宏毅2021春季机器学习课程课件及作业|3193|5|2022-07-03|
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|11|[apachecn/Interview](https://github.com/apachecn/Interview)|Interview = 简历指南 + 算法题 + 八股文 + 源码分析|7820|4|2022-11-26|
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|12|[Charmve/computer-vision-in-action](https://github.com/Charmve/computer-vision-in-action)|学习闭环《计算机视觉实战演练：算法与应用》中文电子书、源码、读者交流社区（持续更新中 ...） 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页|1808|3|2022-11-21|
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|13|[yidao620c/python3-cookbook](https://github.com/yidao620c/python3-cookbook)|《Python Cookbook》 3rd Edition Translation|10523|3|2022-12-01|
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|14|[xianhu/LearnPython](https://github.com/xianhu/LearnPython)|以撸代码的形式学习Python|6572|3|2022-10-04|
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|15|[datawhalechina/joyful-pandas](https://github.com/datawhalechina/joyful-pandas)|pandas中文教程|3585|3|2022-11-05|
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|16|[datawhalechina/competition-baseline](https://github.com/datawhalechina/competition-baseline)|数据科学竞赛知识、代码、思路|3181|3|2022-10-13|
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|17|[jm199504/Financial-Knowledge-Graphs](https://github.com/jm199504/Financial-Knowledge-Graphs)|小型金融知识图谱构建流程|1979|2|2022-10-11|
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|18|[datawhalechina/thorough-pytorch](https://github.com/datawhalechina/thorough-pytorch)|PyTorch入门教程，在线阅读地址：https://datawhalechina.github.io/thorough-pytorch/|754|2|2022-12-08|
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|19|[gedeck/practical-statistics-for-data-scientists](https://github.com/gedeck/practical-statistics-for-data-scientists)|Code repository for O'Reilly book|1661|2|2022-08-05|
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|20|[km1994/NLP-Interview-Notes](https://github.com/km1994/NLP-Interview-Notes)|该仓库主要记录 NLP 算法工程师相关的面试题|1429|2|2022-10-04|
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|21|[PaddlePaddle/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|1892|2|2022-11-30|
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|22|[virginiakm1988/ML2022-Spring](https://github.com/virginiakm1988/ML2022-Spring)|**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2022 Spring|599|2|2022-06-10|
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|23|[fengdu78/WZU-machine-learning-course](https://github.com/fengdu78/WZU-machine-learning-course)|温州大学《机器学习》课程资料（代码、课件等）|1217|2|2022-09-13|
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|24|[charliedream1/ai_quant_trade](https://github.com/charliedream1/ai_quant_trade)|(Eng. Incl.) 股票AI操盘手：包含股票知识、策略实例、机器学习、深度学习、C++部署和聚宽实例代码等，可以方便学习、模拟及实盘交易|109|1|2022-12-08|
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|25|[SMILELab-FL/FedLab](https://github.com/SMILELab-FL/FedLab)|A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.|343|1|2022-11-30|
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|26|[AccumulateMore/CV](https://github.com/AccumulateMore/CV)|✔️最全面的 深度学习CV 笔记【吴恩达 深度学习】【李沐 动手学深度学习】【我是土堆 Pytorch】|281|1|2022-10-25|
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|27|[xinychen/latex-cookbook](https://github.com/xinychen/latex-cookbook)|LaTeX论文写作教程 (中文版)|473|1|2022-08-06|
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|28|[liuyubobobo/Play-with-Machine-Learning-Algorithms](https://github.com/liuyubobobo/Play-with-Machine-Learning-Algorithms)|Code of my MOOC Course <Play with Machine Learning Algorithms>. Updated contents and practices are also included. 我在慕课网上的课程《Python3 入门机器学习》示例代码。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。|1172|1|2022-08-22|
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|29|[huaweicloud/ModelArts-Lab](https://github.com/huaweicloud/ModelArts-Lab)|ModelArts-Lab是示例代码库。更多AI开发学习交流信息，请访问华为云AI开发者社区：huaweicloud.ai|916|1|2022-11-04|
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|30|[luwill/Machine_Learning_Code_Implementation](https://github.com/luwill/Machine_Learning_Code_Implementation)|Mathematical derivation and pure Python code implementation of machine learning algorithms.|1332|1|2022-10-23|
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|31|[openvinotoolkit/openvino_notebooks](https://github.com/openvinotoolkit/openvino_notebooks)|📚 Jupyter notebook tutorials for OpenVINO™|819|1|2022-12-08|
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|32|[ga642381/ML2021-Spring](https://github.com/ga642381/ML2021-Spring)|**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2021 Spring|547|1|2022-07-26|
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|33|[DataXujing/YOLO-v5](https://github.com/DataXujing/YOLO-v5)|:art: Pytorch YOLO v5 训练自己的数据集超详细教程！！！ :art: (提供PDF训练教程下载）|713|1|2022-06-22|
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|34|[CLUEbenchmark/pCLUE](https://github.com/CLUEbenchmark/pCLUE)|pCLUE: 1000000+多任务提示学习数据集|53|1|2022-10-04|
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|35|[nndl/practice-in-paddle](https://github.com/nndl/practice-in-paddle)|《神经网络与深度学习》案例与实践|190|1|2022-11-23|
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|36|[advboxes/AdvBox](https://github.com/advboxes/AdvBox)|Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. ...|1272|1|2022-12-08|
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|37|[CNFeffery/DataScienceStudyNotes](https://github.com/CNFeffery/DataScienceStudyNotes)|这个仓库保管从（数据科学学习手札69）开始的所有代码、数据等相关附件内容|956|1|2022-12-02|
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|38|[datawhalechina/statistical-learning-method-solutions-manual](https://github.com/datawhalechina/statistical-learning-method-solutions-manual)|《统计学习方法》（第二版）习题解答，在线阅读地址：https://datawhalechina.github.io/statistical-learning-method-solutions-manual|1031|1|2022-12-01|
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|39|[szcf-weiya/ESL-CN](https://github.com/szcf-weiya/ESL-CN)|The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。|2091|1|2022-10-30|
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|40|[datawhalechina/machine-learning-toy-code](https://github.com/datawhalechina/machine-learning-toy-code)|《机器学习》（西瓜书）代码实战|268|1|2022-06-20|
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|41|[datawhalechina/hands-on-data-analysis](https://github.com/datawhalechina/hands-on-data-analysis)|动手学数据分析以项目为主线，知识点孕育其中，通过边学、边做、边引导来得到更好的学习效果|788|1|2022-09-16|
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|42|[yunwei37/ZJU-CS-GIS-ClassNotes](https://github.com/yunwei37/ZJU-CS-GIS-ClassNotes)|一个浙江大学本科生的计算机、地理信息科学知识库 包含课程资料 学习笔记 大作业等（ 数据结构与算法、人工智能、地理空间数据库、计算机组成、计算机网络、图形学、编译原理等课程）|477|1|2022-06-29|
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|43|[wmpscc/CNN-Series-Getting-Started-and-PyTorch-Implementation](https://github.com/wmpscc/CNN-Series-Getting-Started-and-PyTorch-Implementation)|我的笔记和Demo，包含分类，检测、分割、知识蒸馏。|52|0|2022-06-22|
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|44|[zzy99/competition-solutions](https://github.com/zzy99/competition-solutions)|我的数据竞赛方案总结|27|0|2022-06-21|
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|45|[fry404006308/fry_course_materials](https://github.com/fry404006308/fry_course_materials)|范仁义录播课资料，会依次推出各种完全免费的前端、后端、大数据、人工智能等课程，课程网站： https://fanrenyi.com ； b站课程地址： https://space.bilibili.com/45664489 ；|134|0|2022-07-21|
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|46|[hitlic/python_book](https://github.com/hitlic/python_book)|清华大学出版社《Python从入门到提高》源代码、课件|23|0|2022-08-09|
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|47|[wowchemy/hugo-blog-theme](https://github.com/wowchemy/hugo-blog-theme)|📝 Hugo Academic Blog Theme. 轻松创建一个简约博客. No code, highly customizable using widgets.|76|0|2022-09-25|
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|48|[microsoft/AIforEarthDataSets](https://github.com/microsoft/AIforEarthDataSets)|Notebooks and documentation for AI-for-Earth-managed datasets on Azure|201|0|2022-06-23|
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|49|[cador/Python_Predict_Analysis_Algorithm_Book_Codes](https://github.com/cador/Python_Predict_Analysis_Algorithm_Book_Codes)|《Python预测之美：数据分析与算法实战》书籍代码维护|47|0|2022-11-21|
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|50|[zhiyu1998/Python-Basis-Notes](https://github.com/zhiyu1998/Python-Basis-Notes)|你的Python入门好帮手：一份包含了Python基础学习需要的知识框架 :snake: + 爬虫基础 :spider: + numpy基础 :bar_chart: + pandas基础 :panda_face: + 深度学习 🍥 + 脚本库 📚|59|0|2022-11-29|
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|51|[neolee/wop](https://github.com/neolee/wop)|零基础编程思维与实践课程《欢迎进入编程世界》主站|56|0|2022-11-14|
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|52|[AccumulateMore/Python](https://github.com/AccumulateMore/Python)|✔️最全面的 Python 笔记【马士兵教育】|35|0|2022-11-08|
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|53|[JunyaoHu/CUMT_StudyFiles](https://github.com/JunyaoHu/CUMT_StudyFiles)|本科课程资料|17|0|2022-07-09|
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|54|[realyanyang/disambiguation](https://github.com/realyanyang/disambiguation)|OAG-WhoIsWho 赛道二 代码分享|24|0|2022-06-21|
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|55|[peanutzhen/JnuCS](https://github.com/peanutzhen/JnuCS)|⚡️暨南大学计算机系课程设计/作业/实验资源|18|0|2022-07-25|
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|56|[IKMLab/course_material](https://github.com/IKMLab/course_material)|上課教材的大集合！！！|25|0|2022-12-08|
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|57|[WYGNG/USTC_SSE_AI](https://github.com/WYGNG/USTC_SSE_AI)|中国科学技术大学软件学院人工智能课程|22|0|2022-11-22|
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|58|[AccumulateMore/CPlusPlus](https://github.com/AccumulateMore/CPlusPlus)|✔️最全面的 C++ 笔记 【黑马程序员】|116|0|2022-11-11|
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|59|[hxchua/datadoubleconfirm](https://github.com/hxchua/datadoubleconfirm)|Simple datasets and notebooks for data visualization, statistical analysis and modelling - with write-ups here: http://projectosyo.wix.com/datadoubleconfirm. |46|0|2022-09-02|
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|60|[JULIELab/MEmoLon](https://github.com/JULIELab/MEmoLon)|Repository for our ACL 2020 paper "Learning and Evaluating Emotion Lexicons for 91 Languages"|21|0|2022-12-08|
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|61|[aialgorithm/AiPy](https://github.com/aialgorithm/AiPy)|Python机器学习、深度学习算法开发等学习资源分享|138|0|2022-09-16|
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|62|[NjtechCVLab/Level_1](https://github.com/NjtechCVLab/Level_1)|入门资料|16|0|2022-07-25|
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|63|[SocratesAcademy/css](https://github.com/SocratesAcademy/css)|《计算社会科学》课程|56|0|2022-11-21|
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|64|[Ayusummer/DailyNotes](https://github.com/Ayusummer/DailyNotes)|日常学习记录|4|0|2022-08-01|
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|65|[Relph1119/statistical-learning-method-camp](https://github.com/Relph1119/statistical-learning-method-camp)|统计学习方法训练营课程作业及答案，视频笔记在线阅读地址：https://relph1119.github.io/statistical-learning-method-camp|191|0|2022-11-22|
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|66|[km1994/nlp_paper_study_information_extraction](https://github.com/km1994/nlp_paper_study_information_extraction)|该仓库主要记录 NLP 算法工程师相关的顶会论文研读笔记【信息抽取篇】|18|0|2022-11-14|
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|67|[wanghao15536870732/StudyNotes](https://github.com/wanghao15536870732/StudyNotes)|📖 学习笔记|16|0|2022-07-29|
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|68|[XinetAI/CVX](https://github.com/XinetAI/CVX)|计算机视觉：阅读 & 写作 & 学习|17|0|2022-10-04|
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|69|[ZhiningLiu1998/mesa](https://github.com/ZhiningLiu1998/mesa)|NeurIPS’20 Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. 设计元知识驱动的采样器解决类别不平衡问题|89|0|2022-06-22|
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|70|[fire717/Python-Toolkit](https://github.com/fire717/Python-Toolkit)|轮子/ 常用库/ 书籍笔记/ 小程序|19|0|2022-10-28|
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|71|[zkcpku/cs231n_homework](https://github.com/zkcpku/cs231n_homework)|cs231n作业笔记|4|0|2022-07-06|
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|72|[mc6666/PyTorch_Book](https://github.com/mc6666/PyTorch_Book)|PyTorch 深度學習範例|19|0|2022-11-13|
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|73|[dota2heqiuzhi/dota2_data_analysis_tutorial](https://github.com/dota2heqiuzhi/dota2_data_analysis_tutorial)|《数据分析入门课程》配套代码|102|0|2022-06-21|
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|74|[dmarx/anthology-of-modern-ml](https://github.com/dmarx/anthology-of-modern-ml)|Collection of important articles to be treated as a textbook|54|0|2022-07-09|
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|75|[LinglingGreat/StudySum](https://github.com/LinglingGreat/StudySum)|学习过程中的笔记梳理与总结|9|0|2022-08-02|
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|76|[beiciliang/intro2musictech](https://github.com/beiciliang/intro2musictech)|公众号“无痛入门音乐科技”开源代码|147|0|2022-06-21|
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|77|[zhangjx831/Data-Science-Notes](https://github.com/zhangjx831/Data-Science-Notes)|数据科学与机器学习炼成笔记|122|0|2022-08-10|
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|78|[wss1996/Name-disambiguation](https://github.com/wss1996/Name-disambiguation)|同名论文消歧的工程化方案（参考2019智源-aminer人名消歧竞赛第一名方案）|17|0|2022-07-29|
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|79|[Christmas-Wong/paper_project](https://github.com/Christmas-Wong/paper_project)|论文模型复现|28|0|2022-09-20|
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|80|[newaetech/chipwhisperer-jupyter](https://github.com/newaetech/chipwhisperer-jupyter)|Interactive ChipWhisperer tutorials using Jupyter notebooks.|83|0|2022-07-25|
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|81|[limingzhong61/LearningNotes](https://github.com/limingzhong61/LearningNotes)|学习笔记|24|0|2022-10-11|
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|82|[JamesLavin/my_tech_resources](https://github.com/JamesLavin/my_tech_resources)|List of tech resources future me and other Javascript/Ruby/Python/Elixir/Elm developers might find useful|270|0|2022-11-30|
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|83|[lululxvi/tutorials](https://github.com/lululxvi/tutorials)|Tutorials on deep learning, Python, and dissipative particle dynamics|98|0|2022-07-17|
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|84|[SocratesAcademy/ccbook](https://github.com/SocratesAcademy/ccbook)|Elements of Computational Communication 《计算传播基础》|27|0|2022-07-22|
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|85|[Dreaming-future/Pytorch-Image-Classification](https://github.com/Dreaming-future/Pytorch-Image-Classification)|用于pytorch的图像分类，包含多种模型方法，比如AlexNet，VGG，GoogleNet，ResNet，DenseNet等等，包含可完整运行的代码。除此之外，也有colab的在线运行代码，可以直接在colab在线运行查看结果。也可以迁移到自己的数据集进行迁移学习。|51|0|2022-11-20|
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|86|[zhpmatrix/BERTem](https://github.com/zhpmatrix/BERTem)|论文实现(ACL2019)：《Matching the Blanks: Distributional Similarity for Relation Learning》|152|0|2022-12-08|
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|87|[LawsonAbs/learn](https://github.com/LawsonAbs/learn)|记录python,pytorch,git等工具的学习过程，主要是对该工具常用部分进行实践。|19|0|2022-06-11|
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|88|[shenhao-stu/CS224W-Fall2021](https://github.com/shenhao-stu/CS224W-Fall2021)|🌟🌟CS224W Fall 2021 Stanford 的个人学习路线🌟🌟|3|0|2022-06-10|
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|89|[doocs/deep-learning](https://github.com/doocs/deep-learning)|🙃 深度学习实践与知识总结|85|0|2022-11-19|
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|90|[afunTW/Python-Crawling-Tutorial](https://github.com/afunTW/Python-Crawling-Tutorial)|Python crawling tutorial|60|0|2022-08-19|
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|91|[lijin-THU/notes-python3](https://github.com/lijin-THU/notes-python3)|中文Python 3笔记|104|0|2022-10-20|
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|92|[MachineLP/Spark-](https://github.com/MachineLP/Spark-)|Spark学习笔记|40|0|2022-11-16|
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|93|[napoler/reformer-chinese](https://github.com/napoler/reformer-chinese)|reformer-pytorch中文版本，简单高效的生成模型。类似GPT2的效果|14|0|2022-06-22|
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|94|[rwepa/DataDemo](https://github.com/rwepa/DataDemo)|提供資料集與範例分享.|16|0|2022-12-08|
|
||
|95|[htylab/machine-learning-python](https://github.com/htylab/machine-learning-python)|機器學習: Python|320|0|2022-11-15|
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|96|[EasonQYS/fastpagesJupyter](https://github.com/EasonQYS/fastpagesJupyter)|汉化中文fastpages，能够上传Jupyter的博客网站 A Chinese version of fastpages|14|0|2022-07-22|
|
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|97|[cumtcssuld/RSP_of_CUMTCS](https://github.com/cumtcssuld/RSP_of_CUMTCS)|【矿大计算机学院资源共享计划（Resource SharingPlan of CUMTCS）】本仓库由矿大计算机学院学生会学习部牵头维护，由计算机学院全体同学共建共享。欢迎大家积极的参加到本资源库的建设中来吧！（每当有重大更新，我们都会将整个库克隆到码云，点击下边链接，到我们的码云仓库可以获得更好的下载体验）|68|0|2022-11-22|
|
||
|98|[qiguming/MLAPP_CN_CODE](https://github.com/qiguming/MLAPP_CN_CODE)|《Machine Learning: A Probabilistic Perspective》（Kevin P. Murphy）中文翻译和书中算法的Python实现。|408|0|2022-06-27|
|
||
|99|[wgwang/ccks2020-baseline](https://github.com/wgwang/ccks2020-baseline)|CCKS 2020: 基于本体的金融知识图谱自动化构建技术评测|75|0|2022-07-19|
|
||
|100|[JackonYang/hands-on-deep-learning-using-tensorflow-2.0](https://github.com/JackonYang/hands-on-deep-learning-using-tensorflow-2.0)|重读 CNN 网络的经典论文，并用 tensorflow 2.0 手撸一遍经典模型，感受一下实测数据|10|0|2022-06-22|
|
||
|101|[usstroot/notebook](https://github.com/usstroot/notebook)|学习笔记|9|0|2022-06-21|
|
||
|102|[johnjim0816/rl-tutorials](https://github.com/johnjim0816/rl-tutorials)|basic algorithms of reinforcement learning|114|0|2022-12-08|
|
||
|103|[batermj/data_sciences_campaign](https://github.com/batermj/data_sciences_campaign)|【数据科学家系列课程】|88|0|2022-12-06|
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|104|[oubindo/cs231n-cnn](https://github.com/oubindo/cs231n-cnn)|斯坦福的cs231n课程的assignments，非常好的课程，在这里也要强推|40|0|2022-12-07|
|
||
|105|[zui0711/Z-Lab](https://github.com/zui0711/Z-Lab)|Z Lab数据实验室开源代码汇总|79|0|2022-09-28|
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||
|106|[grandma-tutorial/Stocker](https://github.com/grandma-tutorial/Stocker)|都會阿嬤 Stocker tutorial|17|0|2022-09-25|
|
||
|107|[0809zheng/CS231n-assignment2019](https://github.com/0809zheng/CS231n-assignment2019)|CS231n 2019年春季学期课程作业|111|0|2022-12-08|
|
||
|108|[yaocoder/Architect-CTO-growth](https://github.com/yaocoder/Architect-CTO-growth)|实践及手册撰写：涵盖DevOps，云原生技术，大数据，人工智能，高并发&高性能&高可用服务等|54|0|2022-11-13|
|
||
|109|[bcaso/Computer-Science-Whitelist](https://github.com/bcaso/Computer-Science-Whitelist)|Google 搜索结果中垃圾站点越来越多，于是这个白名单就这么出来了。|36|0|2022-11-22|
|
||
|110|[heucoder/ML-DL_book](https://github.com/heucoder/ML-DL_book)|机器学习、深度学习一些个人认为不错的书籍。|71|0|2022-11-22|
|
||
|111|[jarodHAN/Python-100-Days-master](https://github.com/jarodHAN/Python-100-Days-master)|python100天学习资料|367|0|2022-12-08|
|
||
|112|[HuangCongQing/OpenCV](https://github.com/HuangCongQing/OpenCV)|opencv学习教程 1、人机互动 2、物体识别 3、图像分割 4、人脸识别 5、动作识别 6、运动跟踪 7、机器人 8、运动分析 9、机器视觉 10、结构分析 11、汽车安全驾驶|59|0|2022-12-03|
|
||
|113|[hululuzhu/chinese-ai-writing-share](https://github.com/hululuzhu/chinese-ai-writing-share)|中文AI写作共享（监督学习和迁移学习来写诗或对对子）|56|0|2022-10-08|
|
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|114|[analyticalmindsltd/smote_variants](https://github.com/analyticalmindsltd/smote_variants)|A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features|464|0|2022-12-06|
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|115|[BrikerMan/classic_chinese_punctuate](https://github.com/BrikerMan/classic_chinese_punctuate)|classic Chinese punctuate experiment with keras using daizhige(殆知阁古代文献藏书) dataset|32|0|2022-12-08|
|
||
|116|[xiaomeng79/learning_notes](https://github.com/xiaomeng79/learning_notes)|学习笔记|19|0|2022-11-07|
|
||
|117|[liangruibupt/aws-is-how](https://github.com/liangruibupt/aws-is-how)|Know How Guide and Hands on Guide for AWS|30|0|2022-12-01|
|
||
|118|[familyld/Machine_Learning](https://github.com/familyld/Machine_Learning)|周志华《机器学习》阅读笔记|354|0|2022-06-14|
|
||
|119|[zhangqizky/ManTra_Net_Test_Demo](https://github.com/zhangqizky/ManTra_Net_Test_Demo)|🌹2019年CVPR论文：ManTra-Net: Manipulation Tracing Network For Detection And Localization of Image Forgeries With Anomalous Features |33|0|2022-11-21|
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|120|[unimauro/QuantumResources](https://github.com/unimauro/QuantumResources)|Here Quantum Resources like: Book, Papers, Videos|21|0|2022-11-18|
|
||
|121|[ForeverHaibara/Fudan-Courses](https://github.com/ForeverHaibara/Fudan-Courses)|Notes for Courses in School of Data Science, Fudan University. 复旦大学数据科学与大数据技术专业（复旦大数据）学习笔记。|21|0|2022-12-03|
|
||
|122|[bobo0810/PytorchNetHub](https://github.com/bobo0810/PytorchNetHub)|项目注释+论文复现+算法竞赛+Pytorch实践|465|0|2022-12-02|
|
||
|123|[xieliaing/CausalInferenceIntro](https://github.com/xieliaing/CausalInferenceIntro)|Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure|86|0|2022-07-31|
|
||
|124|[Valuebai/learn-NLP-luhuibo](https://github.com/Valuebai/learn-NLP-luhuibo)|记录学习NLP之路，一起加油|13|0|2022-06-21|
|
||
|125|[AccumulateMore/OpenCV](https://github.com/AccumulateMore/OpenCV)|✔️最全面的 OpenCV 笔记【咕泡唐宇迪】|108|0|2022-11-08|
|
||
|126|[HuangCongQing/3D-Point-Clouds](https://github.com/HuangCongQing/3D-Point-Clouds)|🔥3D点云目标检测&语义分割(深度学习)-SOTA方法,代码,论文,数据集等|162|0|2022-12-01|
|
||
|127|[W-caner/ML_class](https://github.com/W-caner/ML_class)|学堂在线《机器学习》实验课by张敏老师|9|0|2022-07-30|
|
||
|128|[yangqy1110/Diffusion-Models](https://github.com/yangqy1110/Diffusion-Models)|扩散模型原理和pytorch代码实现初学资料汇总|31|0|2022-10-23|
|
||
|129|[qiwsir/MML](https://github.com/qiwsir/MML)|《机器学习数学基础》源码|18|0|2022-07-15|
|
||
|130|[yaoweizhang/LHY2022-SPRING](https://github.com/yaoweizhang/LHY2022-SPRING)|李宏毅（Hung-yi Lee) 2022年春季机器学习课程，包括课件和作业，|27|0|2022-09-05|
|
||
|131|[somenzz/tutorial](https://github.com/somenzz/tutorial)|实用的关于 Python 的微教程，动画展示。Useful tutorial on Python.|36|0|2022-12-04|
|
||
|132|[aialgorithm/Blog](https://github.com/aialgorithm/Blog)|Python机器学习算法技术博客，有原创干货！有code实践！ 【更多内容敬请关注公众号 "算法进阶"】|382|0|2022-12-01|
|
||
|133|[hanzhenlei767/NLP_Learn](https://github.com/hanzhenlei767/NLP_Learn)|NLP学习笔记-前沿追踪|24|0|2022-11-21|
|
||
|134|[zhangjunhd/reading-notes](https://github.com/zhangjunhd/reading-notes)|张俊的读书笔记|142|0|2022-06-23|
|
||
|135|[dream80/TonyColab](https://github.com/dream80/TonyColab)|各种牛逼项目的Colab脚本集合！|45|0|2022-12-02|
|
||
|136|[Relph1119/my-team-learning](https://github.com/Relph1119/my-team-learning)|我的Datawhale组队学习，在线阅读地址：https://relph1119.github.io/my-team-learning|19|0|2022-09-14|
|
||
|137|[evenchange4/nextjs-tfjs-cnn](https://github.com/evenchange4/nextjs-tfjs-cnn)|🐕 🐈 Classifier using Keras VGG16 transfer learning with kaggle dataset.|14|0|2022-06-18|
|
||
|138|[Relph1119/deeplearning-with-tensorflow-notes](https://github.com/Relph1119/deeplearning-with-tensorflow-notes)|龙曲良《TensorFlow深度学习》学习笔记及代码，采用TensorFlow2.0.0版本|159|0|2022-12-08|
|
||
|
||
<div align="center">
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<p><sub>↓ -- 感谢读者 -- ↓</sub></p>
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榜单持续更新，如有帮助请加星收藏，方便后续浏览，感谢你的支持！
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