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<a href="https://github.com/kon9chunkit/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>
# 中文总榜 > 资料类 > Jupyter Notebook
<sub>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>
|#|Repository|Description|Stars|Updated|
|:-|:-|:-|:-|:-|
|1|[MLEveryday/100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|100-Days-Of-ML-Code中文版|16790|2021-08-11|
|2|[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|16098|2021-12-16|
|3|[zergtant/pytorch-handbook](https://github.com/zergtant/pytorch-handbook)|pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行|15820|2021-10-25|
|4|[ShusenTang/Dive-into-DL-PyTorch](https://github.com/ShusenTang/Dive-into-DL-PyTorch)|本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。|14235|2021-10-14|
|5|[fastai/fastbook](https://github.com/fastai/fastbook)|The fastai book, published as Jupyter Notebooks|14000|2021-12-07|
|6|[dragen1860/Deep-Learning-with-TensorFlow-book](https://github.com/dragen1860/Deep-Learning-with-TensorFlow-book)|深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.|12106|2021-08-30|
|7|[rasbt/python-machine-learning-book](https://github.com/rasbt/python-machine-learning-book)|The "Python Machine Learning (1st edition)" book code repository and info resource|11429|2021-07-30|
|8|[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。|10827|2021-06-26|
|9|[yidao620c/python3-cookbook](https://github.com/yidao620c/python3-cookbook)|《Python Cookbook》 3rd Edition Translation|9692|2021-08-27|
|10|[apachecn/Interview](https://github.com/apachecn/Interview)|Interview = 简历指南 + LeetCode + Kaggle|7207|2021-11-07|
|11|[Mikoto10032/DeepLearning](https://github.com/Mikoto10032/DeepLearning)|深度学习入门教程, 优秀文章, Deep Learning Tutorial|6783|2021-10-21|
|12|[fengdu78/Data-Science-Notes](https://github.com/fengdu78/Data-Science-Notes)|数据科学的笔记以及资料搜集|6074|2021-08-16|
|13|[xianhu/LearnPython](https://github.com/xianhu/LearnPython)|以撸代码的形式学习Python|6040|2021-11-11|
|14|[snowkylin/tensorflow-handbook](https://github.com/snowkylin/tensorflow-handbook)|简单粗暴 TensorFlow 2 A Concise Handbook of TensorFlow 2 一本简明的 TensorFlow 2 入门指导教程|3616|2021-09-04|
|15|[TrickyGo/Dive-into-DL-TensorFlow2.0](https://github.com/TrickyGo/Dive-into-DL-TensorFlow2.0)|本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的认可|3380|2021-08-31|
|16|[datawhalechina/easy-rl](https://github.com/datawhalechina/easy-rl)|强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/|3004|2021-12-17|
|17|[datawhalechina/joyful-pandas](https://github.com/datawhalechina/joyful-pandas)|pandas中文教程|2788|2021-10-05|
|18|[PaddlePaddle/book](https://github.com/PaddlePaddle/book)|Deep Learning 101 with PaddlePaddle （『飞桨』深度学习框架入门教程）|2621|2021-11-12|
|19|[datawhalechina/competition-baseline](https://github.com/datawhalechina/competition-baseline)|数据科学竞赛知识、代码、思路|2553|2021-12-03|
|20|[zlotus/notes-linear-algebra](https://github.com/zlotus/notes-linear-algebra)|线性代数笔记|2393|2021-12-13|
|21|[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。|1855|2021-11-23|
|22|[xavier-zy/Awesome-pytorch-list-CNVersion](https://github.com/xavier-zy/Awesome-pytorch-list-CNVersion)|Awesome-pytorch-list 翻译工作进行中......|1500|2021-07-26|
|23|[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|1339|2021-06-23|
|24|[Charmve/computer-vision-in-action](https://github.com/Charmve/computer-vision-in-action)|《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|1234|2021-12-14|
|25|[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. ...|1187|2021-09-08|
|26|[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|1097|2021-12-13|
|27|[ben1234560/AiLearning-Theory-Applying](https://github.com/ben1234560/AiLearning-Theory-Applying)|快速上手Ai理论及应用实战：基础知识Basic knowledge、机器学习MachineLearning、深度学习DeepLearning2、自然语言处理BERT，持续更新中。含大量注释及数据集，力求每一位能看懂并复现。|976|2021-10-27|
|28|[zslucky/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|967|2021-10-30|
|29|[matheusfacure/python-causality-handbook](https://github.com/matheusfacure/python-causality-handbook)|Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis. |927|2021-12-19|
|30|[datawhalechina/team-learning-data-mining](https://github.com/datawhalechina/team-learning-data-mining)|主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。|897|2021-12-02|
|31|[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|882|2021-11-26|
|32|[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）|793|2021-12-10|
|33|[wx-chevalier/AI-Series](https://github.com/wx-chevalier/AI-Series)|:books: [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics Fundamentals, Python Practices, NLP Application, etc. 💫 人工智能与深度学习实战，数理统计篇 机器学习篇 深度学习篇 自然语言处理篇 工具 ...|715|2021-11-24|
|34|[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|692|2021-12-05|
|35|[zhouyanasd/or-pandas](https://github.com/zhouyanasd/or-pandas)|【运筹OR帷幄 数据科学】pandas教程系列电子书|667|2021-10-17|
|36|[geektutu/interview-questions](https://github.com/geektutu/interview-questions)|机器学习/深度学习/Python/Go语言面试题笔试题(Machine learning Deep Learning Python and Golang Interview Questions)|657|2021-06-12|
|37|[MemorialCheng/deep-learning-from-scratch](https://github.com/MemorialCheng/deep-learning-from-scratch)|《深度学习入门-基于Python的理论与实现》，包含源代码和高清PDF(带书签)；慕课网imooc《深度学习之神经网络(CNN-RNN-GAN)算法原理-实战》；《菜菜的机器学习sklearn》|642|2021-11-03|
|38|[fly51fly/Practical_Python_Programming](https://github.com/fly51fly/Practical_Python_Programming)|北邮《Python编程与实践》课程资料|641|2021-06-09|
|39|[MorvanZhou/easy-scraping-tutorial](https://github.com/MorvanZhou/easy-scraping-tutorial)|Simple but useful Python web scraping tutorial code. |639|2021-08-18|
|40|[ZhiqingXiao/rl-book](https://github.com/ZhiqingXiao/rl-book)|Source codes for the book "Reinforcement Learning: Theory and Python Implementation"|601|2021-12-12|
|41|[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）|581|2021-12-17|
|42|[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|574|2021-12-17|
|43|[datawhalechina/team-learning-program](https://github.com/datawhalechina/team-learning-program)|主要存储Datawhale组队学习中“编程、数据结构与算法”方向的资料。|570|2021-12-18|
|44|[shibing624/python-tutorial](https://github.com/shibing624/python-tutorial)|Python实用教程，包括：Python基础，Python高级特性，面向对象编程，多线程，数据库，数据科学，Flask，爬虫开发教程。|546|2021-11-05|
|45|[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|497|2021-09-09|
|46|[openvinotoolkit/openvino_notebooks](https://github.com/openvinotoolkit/openvino_notebooks)|📚 A collection of Jupyter notebooks for learning and experimenting with OpenVINO 👓|483|2021-12-19|
|47|[zkywsg/Daily-DeepLearning](https://github.com/zkywsg/Daily-DeepLearning)|🔥机器学习/深度学习/Python/算法面试/自然语言处理教程/剑指offer/machine learning/deeplearning/Python/Algorithm interview/NLP Tutorial|442|2021-07-13|
|48|[bobo0810/PytorchNetHub](https://github.com/bobo0810/PytorchNetHub)|项目注释+论文复现+算法竞赛+Pytorch指北|401|2021-11-05|
|49|[evanzd/ICLR2021-OpenReviewData](https://github.com/evanzd/ICLR2021-OpenReviewData)|Crawl & visualize ICLR papers and reviews.|390|2021-11-09|
|50|[datawhalechina/team-learning-nlp](https://github.com/datawhalechina/team-learning-nlp)|主要存储Datawhale组队学习中“自然语言处理”方向的资料。|388|2021-09-17|
|51|[wolfparticle/machineLearningDeepLearning](https://github.com/wolfparticle/machineLearningDeepLearning)|李宏毅2021机器学习深度学习笔记PPT作业|337|2021-06-14|
|52|[SummerLife/EmbeddedSystem](https://github.com/SummerLife/EmbeddedSystem)|:books: 计算机体系架构、嵌入式系统基础与主流编程语言相关内容总结|321|2021-11-02|
|53|[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。|308|2021-07-14|
|54|[liuhuanshuo/zaoqi-Python](https://github.com/liuhuanshuo/zaoqi-Python)|公众号：早起Python|300|2021-10-20|
|55|[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）|273|2021-12-06|
|56|[ni1o1/pygeo-tutorial](https://github.com/ni1o1/pygeo-tutorial)|Tutorial of geospatial data processing using python 用python分析时空数据的教程(in Chinese and English )|259|2021-11-17|
|57|[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|244|2021-12-12|
|58|[jarodHAN/Python-100-Days-master](https://github.com/jarodHAN/Python-100-Days-master)|python100天学习资料|231|2021-06-02|
|59|[d2l-ai/courses-zh-v2](https://github.com/d2l-ai/courses-zh-v2)|中文版 v2 课程|220|2021-09-14|
|60|[datawhalechina/fantastic-matplotlib](https://github.com/datawhalechina/fantastic-matplotlib)|Matplotlib中文教程，在线阅读地址：https://datawhalechina.github.io/fantastic-matplotlib/|211|2021-08-09|
|61|[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|189|2021-09-08|
|62|[LemenChao/PythonFromDAToDS](https://github.com/LemenChao/PythonFromDAToDS)|图书《Python编程：从数据分析到数据科学》的配套资源|187|2021-10-10|
|63|[datamonday/Time-Series-Analysis-Tutorial](https://github.com/datamonday/Time-Series-Analysis-Tutorial)|时间序列分析教程|182|2021-06-01|
|64|[datawhalechina/team-learning-cv](https://github.com/datawhalechina/team-learning-cv)|主要存储Datawhale组队学习中“计算机视觉”方向的资料。|171|2021-09-06|
|65|[kingname/SourceCodeofMongoRedis](https://github.com/kingname/SourceCodeofMongoRedis)|《左手MongoDB，右手Redis——从入门到商业实战》书籍配套源代码。|165|2021-08-19|
|66|[microsoft/AIforEarthDataSets](https://github.com/microsoft/AIforEarthDataSets)|Notebooks and documentation for AI-for-Earth-managed datasets on Azure|164|2021-12-16|
|67|[fire717/Machine-Learning](https://github.com/fire717/Machine-Learning)|机器学习&深度学习资料笔记&基本算法实现&资源整理（ML / CV / NLP / DM...）|164|2021-11-16|
|68|[mepeichun/Efficient-Neural-Network-Bilibili](https://github.com/mepeichun/Efficient-Neural-Network-Bilibili)|B站Efficient-Neural-Network学习分享的配套代码|158|2021-12-08|
|69|[huangtinglin/Linear-Algebra-and-Its-Applications-notes](https://github.com/huangtinglin/Linear-Algebra-and-Its-Applications-notes)|《线性代数及其应用》笔记|152|2021-09-17|
|70|[sijichun/MathStatsCode](https://github.com/sijichun/MathStatsCode)|Codes for my mathematical statistics course|148|2021-10-25|
|71|[liuhuanshuo/Pandas_Advanced_Exercise](https://github.com/liuhuanshuo/Pandas_Advanced_Exercise)|Pandas进阶修炼300题|140|2021-09-22|
|72|[chansonZ/book-ml-sem](https://github.com/chansonZ/book-ml-sem)|《机器学习：软件工程方法与实现》Method and implementation of machine learning software engineering|123|2021-11-29|
|73|[beiciliang/intro2musictech](https://github.com/beiciliang/intro2musictech)|公众号“无痛入门音乐科技”开源代码|119|2021-10-31|
|74|[fancyerii/deep_learning_theory_and_practice](https://github.com/fancyerii/deep_learning_theory_and_practice)|《深度学习理论与实战：基础篇》代码|118|2021-06-07|
|75|[oldratlee/software-practice-thoughts](https://github.com/oldratlee/software-practice-thoughts)|📚 🐣 软件实践文集。主题不限，思考讨论有趣有料就好，包含如 系统的模型分析/量化分析、开源漫游者指南、软件可靠性设计实践…… 🥤|106|2021-12-02|
|76|[datawhalechina/machine-learning-toy-code](https://github.com/datawhalechina/machine-learning-toy-code)|《机器学习》（西瓜书）代码实战|97|2021-12-17|
|77|[0809zheng/CS231n-assignment2019](https://github.com/0809zheng/CS231n-assignment2019)|CS231n 2019年春季学期课程作业|95|2021-11-08|
|78|[xuwening/blog](https://github.com/xuwening/blog)|对过往做做总结|90|2021-09-16|
|79|[sherlcok314159/ML](https://github.com/sherlcok314159/ML)|此仓库将介绍Deep Learning 所需要的基础知识以及NLP方面的模型原理到项目实操 : )|88|2021-12-15|
|80|[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！ |88|2021-12-17|
|81|[Divsigma/2020-cs213n](https://github.com/Divsigma/2020-cs213n)|一些公开课的笔记及作业|87|2021-11-13|
|82|[ZitongLu1996/Python-EEG-Handbook](https://github.com/ZitongLu1996/Python-EEG-Handbook)|Python脑电数据处理中文手册 - A Chinese handbook for EEG data analysis based on Python|86|2021-09-23|
|83|[batermj/data_sciences_campaign](https://github.com/batermj/data_sciences_campaign)|【数据科学家系列课程】|84|2021-12-19|
|84|[China-ChallengeHub/ChallengeHub-Baselines](https://github.com/China-ChallengeHub/ChallengeHub-Baselines)|ChallengeHub开源的各大比赛baseline集合|74|2021-09-24|
|85|[zhangjunhd/reading-notes](https://github.com/zhangjunhd/reading-notes)|张俊的读书笔记|66|2021-12-17|
|86|[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|64|2021-08-18|
|87|[shibing624/nlp-tutorial](https://github.com/shibing624/nlp-tutorial)|自然语言处理（NLP）教程，包括：词向量，词法分析，预训练语言模型，文本分类，文本语义匹配，信息抽取，翻译，对话。|63|2021-10-21|
|88|[xinychen/latex-cookbook](https://github.com/xinychen/latex-cookbook)|LaTeX论文写作教程 (中文版)|63|2021-12-11|
|89|[afunTW/Python-Crawling-Tutorial](https://github.com/afunTW/Python-Crawling-Tutorial)|Python crawling tutorial|62|2021-12-13|
|90|[shiyanlou/louplus-dm](https://github.com/shiyanlou/louplus-dm)|实验楼 《楼+ 数据分析与挖掘实战》课程挑战作业参考答案|61|2021-08-16|
|91|[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|57|2021-12-10|
|92|[HuangCongQing/3D-Point-Clouds](https://github.com/HuangCongQing/3D-Point-Clouds)|🔥3D点云目标检测&语义分割-SOTA方法,代码,论文,数据集等|56|2021-10-13|
|93|[newaetech/chipwhisperer-jupyter](https://github.com/newaetech/chipwhisperer-jupyter)|Interactive ChipWhisperer tutorials using Jupyter notebooks.|54|2021-12-08|
|94|[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。|54|2021-11-08|
|95|[wwtm/gitpython_examples](https://github.com/wwtm/gitpython_examples)|some interesting python examples|52|2021-10-16|
|96|[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）|51|2021-11-28|
|97|[hiDaDeng/DaDengAndHisPython](https://github.com/hiDaDeng/DaDengAndHisPython)|【微信公众号：大邓和他的python】, Python语法快速入门https://www.bilibili.com/video/av44384851 Python网络爬虫快速入门https://www.bilibili.com/video/av72010301, 我的联系邮箱[email protected]|51|2021-12-19|
|98|[xiaoxiaoyao/MyApp](https://github.com/xiaoxiaoyao/MyApp)|随便写的各种，点链接可以进入我的知乎|51|2021-11-19|
|99|[Sharpiless/yolov5-distillation-5.0](https://github.com/Sharpiless/yolov5-distillation-5.0)|yolov5 5.0 version distillation yolov5 5.0版本知识蒸馏，yolov5l >> yolov5s|49|2021-07-29|
|100|[Amberlan1001/eat_tensorflow2_in_30_days_ipynb](https://github.com/Amberlan1001/eat_tensorflow2_in_30_days_ipynb)|30天掌握Tensorflow2.1 Jupyter Notebook 版|49|2021-12-17|
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