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# 中文增速榜 > 资料类 > Jupyter Notebook
<sub>数据更新: 2022-02-07&nbsp;&nbsp;&nbsp;/&nbsp;&nbsp;&nbsp;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|Average daily growth|Updated|
|:-|:-|:-|:-|:-|:-|
|1|[fastai/fastbook](https://github.com/fastai/fastbook)|The fastai book, published as Jupyter Notebooks|14229|20|2022-01-29|
|2|[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|16008|14|2021-10-25|
|3|[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.|12190|13|2021-08-30|
|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。|14464|13|2021-10-14|
|5|[MLEveryday/100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|100-Days-Of-ML-Code中文版|16985|13|2021-08-11|
|6|[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。|11111|12|2021-12-24|
|7|[selfteaching/the-craft-of-selfteaching](https://github.com/selfteaching/the-craft-of-selfteaching)|One has no future if one couldn't teach themself.|13068|12|2022-02-01|
|8|[fengdu78/Data-Science-Notes](https://github.com/fengdu78/Data-Science-Notes)|数据科学的笔记以及资料搜集|6229|7|2021-08-16|
|9|[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).|12312|7|2021-11-24|
|10|[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/|3267|6|2022-02-06|
|11|[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|1295|5|2022-01-11|
|12|[apachecn/Interview](https://github.com/apachecn/Interview)|Interview = 简历指南 + 算法题 + 八股文 + 源码分析|7252|5|2022-01-19|
|13|[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|16518|5|2022-01-29|
|14|[Mikoto10032/DeepLearning](https://github.com/Mikoto10032/DeepLearning)|深度学习入门教程, 优秀文章, Deep Learning Tutorial|6996|5|2021-12-27|
|15|[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|1626|5|2022-02-05|
|16|[yidao620c/python3-cookbook](https://github.com/yidao620c/python3-cookbook)|《Python Cookbook》 3rd Edition Translation|9787|4|2022-02-01|
|17|[datawhalechina/joyful-pandas](https://github.com/datawhalechina/joyful-pandas)|pandas中文教程|2859|4|2021-10-05|
|18|[xianhu/LearnPython](https://github.com/xianhu/LearnPython)|以撸代码的形式学习Python|6110|3|2021-11-11|
|19|[datawhalechina/competition-baseline](https://github.com/datawhalechina/competition-baseline)|数据科学竞赛知识、代码、思路|2611|3|2022-01-29|
|20|[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|3651|3|2021-09-04|
|21|[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）|903|3|2022-01-24|
|22|[gedeck/practical-statistics-for-data-scientists](https://github.com/gedeck/practical-statistics-for-data-scientists)|Code repository for O'Reilly book|1101|2|2022-01-28|
|23|[openvinotoolkit/openvino_notebooks](https://github.com/openvinotoolkit/openvino_notebooks)|📚 A collection of Jupyter notebooks for learning and experimenting with OpenVINO 👓|525|2|2022-02-06|
|24|[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。|946|2|2021-12-02|
|25|[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|1196|2|2022-02-03|
|26|[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|3406|2|2021-08-31|
|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。|1014|2|2021-10-27|
|28|[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。|587|1|2022-02-06|
|29|[ssssww0905/-PyTorch-](https://github.com/ssssww0905/-PyTorch-)|【PyTorch】手把手教你跑通第一个神经网络|53|1|2022-01-03|
|30|[xinychen/latex-cookbook](https://github.com/xinychen/latex-cookbook)|LaTeX论文写作教程 (中文版)|220|1|2022-02-06|
|31|[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/|248|1|2022-01-07|
|32|[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|891|1|2021-11-26|
|33|[zlotus/notes-linear-algebra](https://github.com/zlotus/notes-linear-algebra)|线性代数笔记|2444|1|2021-12-13|
|34|[luwill/Machine_Learning_Code_Implementation](https://github.com/luwill/Machine_Learning_Code_Implementation)|Mathematical derivation and pure Python code implementation of machine learning algorithms.|954|1|2022-02-05|
|35|[bighuang624/Andrew-Ng-Deep-Learning-notes](https://github.com/bighuang624/Andrew-Ng-Deep-Learning-notes)|吴恩达《深度学习》系列课程笔记及代码   Notes in Chinese for Andrew Ng Deep Learning Course|867|1|2022-01-19|
|36|[ZhiqingXiao/rl-book](https://github.com/ZhiqingXiao/rl-book)|Source codes for the book "Reinforcement Learning: Theory and Python Implementation"|612|1|2022-02-06|
|37|[PaddlePaddle/book](https://github.com/PaddlePaddle/book)|Deep Learning 101 with PaddlePaddle （『飞桨』深度学习框架入门教程）|2632|1|2021-11-12|
|38|[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》|695|1|2021-11-03|
|39|[d2l-ai/courses-zh-v2](https://github.com/d2l-ai/courses-zh-v2)|中文版 v2 课程|244|1|2021-09-14|
|40|[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）|608|1|2021-12-17|
|41|[liuhuanshuo/Pandas_Advanced_Exercise](https://github.com/liuhuanshuo/Pandas_Advanced_Exercise)|Pandas进阶修炼300题|157|1|2021-09-22|
|42|[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. ...|1200|1|2022-01-13|
|43|[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|730|1|2022-01-12|
|44|[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|683|1|2021-10-17|
|45|[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|638|1|2022-01-21|
|46|[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。|1896|1|2022-01-14|
|47|[datawhalechina/machine-learning-toy-code](https://github.com/datawhalechina/machine-learning-toy-code)|《机器学习》（西瓜书）代码实战|131|1|2022-01-04|
|48|[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|545|1|2021-09-09|
|49|[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。|419|1|2021-09-17|
|50|[evanzd/ICLR2021-OpenReviewData](https://github.com/evanzd/ICLR2021-OpenReviewData)|Crawl & visualize ICLR papers and reviews.|401|1|2021-11-09|
|51|[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。|49|0|2022-01-21|
|52|[zzy99/competition-solutions](https://github.com/zzy99/competition-solutions)|我的数据竞赛方案总结|17|0|2021-11-16|
|53|[fry404006308/fry_course_materials](https://github.com/fry404006308/fry_course_materials)|范仁义录播课资料|18|0|2022-01-14|
|54|[neolee/pilot-student](https://github.com/neolee/pilot-student)|“进入编程世界的第一课” 的学习用书|79|0|2022-01-28|
|55|[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|14|0|2022-01-13|
|56|[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。|562|0|2021-11-05|
|57|[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.|52|0|2021-12-11|
|58|[binzhouchn/machine_learning](https://github.com/binzhouchn/machine_learning)|抽象来讲，机器学习问题是把数据转换成信息再提炼到知识的过程，特征是“数据-->信息”的过程，决定了结果的上限，而分类器是“信息-->知识”的过程，则是去逼近这个上限|18|0|2021-10-15|
|59|[sijichun/MathStatsCode](https://github.com/sijichun/MathStatsCode)|Codes for my mathematical statistics course|151|0|2021-12-27|
|60|[ymzis69/gddw_track3](https://github.com/ymzis69/gddw_track3)|阿里云天池广东电网识别挑战赛（赛道三） 亚军方案分享|11|0|2021-09-15|
|61|[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。|186|0|2021-09-06|
|62|[microsoft/AIforEarthDataSets](https://github.com/microsoft/AIforEarthDataSets)|Notebooks and documentation for AI-for-Earth-managed datasets on Azure|174|0|2022-01-07|
|63|[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|34|0|2021-08-25|
|64|[zhiyu1998/Python-Basis-Notes](https://github.com/zhiyu1998/Python-Basis-Notes)|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:|45|0|2021-12-11|
|65|[Mazeqi/PaperNote](https://github.com/Mazeqi/PaperNote)|阅读论文的一些笔记|11|0|2021-12-09|
|66|[reganzm/Learn-Pytorch-And-Become-A-Data-Scientist](https://github.com/reganzm/Learn-Pytorch-And-Become-A-Data-Scientist)|《学好Pytorch成为数据科学家》书籍随书代码|19|0|2021-10-21|
|67|[johnnychen94/Julia_and_its_applications](https://github.com/johnnychen94/Julia_and_its_applications)|2021 年《Julia 语言及其应用》系列讲座的材料|39|0|2021-12-05|
|68|[OUCTheoryGroup/colab_demo](https://github.com/OUCTheoryGroup/colab_demo)|中国海洋大学视觉实验室前沿理论小组 pytorch 学习|51|0|2021-10-16|
|69|[BrikerMan/tf2-101](https://github.com/BrikerMan/tf2-101)|Repository for Book 《TensorFlow 2.0 入门实践》|11|0|2021-10-28|
|70|[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。|168|0|2021-08-19|
|71|[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|15|0|2022-01-13|
|72|[jinhualee/datashine](https://github.com/jinhualee/datashine)|《Python统计与数据分析实战》课程代码，包含了大部分统计与非参数统计和数据分析的模型、算法。回归分析、方差分析、点估计、假设检验、主成分分析、因子分析、聚类分析、判别分析、对数线性模型、分位回归模型以及列联表分析、非参数平滑、非参数密度估计等各种非参数统计方法。|37|0|2021-08-16|
|73|[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. |35|0|2022-02-06|
|74|[howie6879/pylab](https://github.com/howie6879/pylab)|和Python相关的学习笔记：机器学习、算法、进阶书籍、文档，博客地址：https://www.howie6879.cn|39|0|2022-01-27|
|75|[JULIELab/MEmoLon](https://github.com/JULIELab/MEmoLon)|Repository for our ACL 2020 paper "Learning and Evaluating Emotion Lexicons for 91 Languages"|19|0|2022-01-21|
|76|[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|40|0|2021-12-27|
|77|[NjtechCVLab/Level_1](https://github.com/NjtechCVLab/Level_1)|入门资料|12|0|2021-11-29|
|78|[SocratesAcademy/css](https://github.com/SocratesAcademy/css)|《计算社会科学》课程|45|0|2022-02-06|
|79|[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|0|2022-01-21|
|80|[xiaoyusmd/PythonDataScience](https://github.com/xiaoyusmd/PythonDataScience)|Python数据科学系专栏（pandas、Numpy、SKlearn、Matplotlib）、实战项目（代码、讲解、数据集）|53|0|2022-01-23|
|81|[zhiyu1998/Computer-Science-Learn-Notes](https://github.com/zhiyu1998/Computer-Science-Learn-Notes)|我的CS（Computer Science）生涯学习/读书笔记，包含：Java、Spring系列、Python、Golang、深度学习、数据结构等|25|0|2022-01-27|
|82|[wanghao15536870732/StudyNotes](https://github.com/wanghao15536870732/StudyNotes)|📖 学习笔记|10|0|2021-11-08|
|83|[fly51fly/Principle_of_Web_Search_2021](https://github.com/fly51fly/Principle_of_Web_Search_2021)|北邮《网络搜索引擎原理》课程(2021)|41|0|2021-11-05|
|84|[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|75|0|2021-12-23|
|85|[fire717/Python-Toolkit](https://github.com/fire717/Python-Toolkit)|轮子/ 常用库/ 书籍笔记/ 小程序|16|0|2022-01-26|
|86|[rhidra/autopilot](https://github.com/rhidra/autopilot)|A UAV autonomous navigation autopilot, made with ROS, MAVROS, PX4 and Gazebo. Check out my master thesis in the repo for more info.|10|0|2021-09-23|
|87|[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|189|0|2021-10-10|
|88|[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|130|0|2021-11-29|
|89|[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|51|0|2021-12-17|
|90|[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|84|0|2022-01-07|
|91|[hzcforever/Something](https://github.com/hzcforever/Something)|面试知识点 + 笔试刷题总结。|21|0|2021-09-15|
|92|[dmarx/anthology-of-modern-ml](https://github.com/dmarx/anthology-of-modern-ml)|Collection of important articles to be treated as a textbook|20|0|2022-01-14|
|93|[tsaac/Python](https://github.com/tsaac/Python)|YINUXY的python脚本分享|23|0|2021-09-20|
|94|[beiciliang/intro2musictech](https://github.com/beiciliang/intro2musictech)|公众号“无痛入门音乐科技”开源代码|125|0|2021-10-31|
|95|[zhangjx831/Data-Science-Notes](https://github.com/zhangjx831/Data-Science-Notes)|数据科学与机器学习炼成笔记|53|0|2022-01-29|
|96|[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）|14|0|2021-08-25|
|97|[newaetech/chipwhisperer-jupyter](https://github.com/newaetech/chipwhisperer-jupyter)|Interactive ChipWhisperer tutorials using Jupyter notebooks.|59|0|2022-01-30|
|98|[HeXavi8/Mathematical-Modeling](https://github.com/HeXavi8/Mathematical-Modeling)|A sharing of the learning process of mathematical modeling 数学建模常用工具模型算法分享：数学建模竞赛优秀论文，数学建模常用算法模型，LaTeX论文模板，SPSS工具分享。|26|0|2021-11-20|
|99|[eagle-dai/OptimizingSoftwareInCpp](https://github.com/eagle-dai/OptimizingSoftwareInCpp)|Optimizing Software In C++ 非正式中文翻译|23|0|2022-01-17|
|100|[Relph1119/Pytorch-Camp](https://github.com/Relph1119/Pytorch-Camp)|深度之眼《Pytorch框架训练营》|14|0|2021-10-12|
|101|[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|249|0|2022-01-24|
|102|[lululxvi/tutorials](https://github.com/lululxvi/tutorials)|Tutorials on deep learning, Python, and dissipative particle dynamics|51|0|2021-12-14|
|103|[SocratesAcademy/ccbook](https://github.com/SocratesAcademy/ccbook)|Elements of Computational Communication 《计算传播基础》|25|0|2021-09-27|
|104|[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。|14|0|2022-01-18|
|105|[afunTW/Python-Crawling-Tutorial](https://github.com/afunTW/Python-Crawling-Tutorial)|Python crawling tutorial|61|0|2022-01-26|
|106|[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。|73|0|2021-10-21|
|107|[MachineLP/Spark-](https://github.com/MachineLP/Spark-)|Spark学习笔记|42|0|2021-12-09|
|108|[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|12|0|2021-09-25|
|109|[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|160|0|2021-09-17|
|110|[whyAndBetter/python_grammar](https://github.com/whyAndBetter/python_grammar)|Python的基础语法学习|15|0|2022-01-09|
|111|[rwepa/DataDemo](https://github.com/rwepa/DataDemo)|提供資料集與範例分享.|13|0|2021-11-11|
|112|[skywateryang/timeseries101](https://github.com/skywateryang/timeseries101)|本教程独立网站已上线|57|0|2021-12-28|
|113|[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）|52|0|2022-01-13|
|114|[km1994/GCN_study](https://github.com/km1994/GCN_study)|GCN 入门学习教程|44|0|2022-01-19|
|115|[jcchan23/CoMPT](https://github.com/jcchan23/CoMPT)|Code of our IJCAI2021 paper: "Learning Attributed Graph Representation with Communicative Message Passing Transformer"|33|0|2021-09-08|
|116|[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|172|0|2021-12-08|
|117|[mindspore-ai/course](https://github.com/mindspore-ai/course)|MindSpore course|33|0|2021-11-03|
|118|[johnjim0816/rl-tutorials](https://github.com/johnjim0816/rl-tutorials)|basic algorithms of reinforcement learning|39|0|2021-12-29|
|119|[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|0|2022-01-15|
|120|[1am9trash/Hung_Yi_Lee_ML_2021](https://github.com/1am9trash/Hung_Yi_Lee_ML_2021)|李宏毅教授 2021年機器學習 作業與筆記匯總|17|0|2021-09-17|
|121|[batermj/data_sciences_campaign](https://github.com/batermj/data_sciences_campaign)|【数据科学家系列课程】|85|0|2022-02-06|
|122|[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|39|0|2022-01-21|
|123|[lvyufeng/d2l-mindspore](https://github.com/lvyufeng/d2l-mindspore)|《动手学深度学习》的MindSpore实现。供MindSpore学习者配合李沐老师课程使用。|16|0|2022-02-02|
|124|[liuhuanshuo/zaoqi-Python](https://github.com/liuhuanshuo/zaoqi-Python)|公众号：早起Python|305|0|2021-10-20|
|125|[MorvanZhou/easy-scraping-tutorial](https://github.com/MorvanZhou/easy-scraping-tutorial)|Simple but useful Python web scraping tutorial code. |647|0|2021-08-18|
|126|[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thunderhit@qq.com|56|0|2021-12-28|
|127|[0809zheng/CS231n-assignment2019](https://github.com/0809zheng/CS231n-assignment2019)|CS231n 2019年春季学期课程作业|97|0|2022-01-21|
|128|[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。|56|0|2022-01-13|
|129|[HuangCongQing/CS231n_Spring_2019](https://github.com/HuangCongQing/CS231n_Spring_2019)|CS231n_Spring（2019年秋季）计算机视觉课程|18|0|2022-01-09|
|130|[LaoGong-zp/Transformer](https://github.com/LaoGong-zp/Transformer)| Learning materials of Transformer, including my code, XMind, PDF and so on|43|0|2021-09-28|
|131|[Divsigma/2020-cs213n](https://github.com/Divsigma/2020-cs213n)|一些公开课的笔记及作业|93|0|2021-11-13|
|132|[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...）|167|0|2022-01-31|
|133|[ZhangXinNan/DL-with-Python-and-PyTorch](https://github.com/ZhangXinNan/DL-with-Python-and-PyTorch)|《Python深度学习基于PyTorch》 Deep Learning with Python and PyTorch 作者：吴茂贵 郁明敏 杨本法 李涛 张粤磊 等|38|0|2021-08-08|
|134|[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|29|0|2022-01-21|
|135|[xiaomeng79/learning_notes](https://github.com/xiaomeng79/learning_notes)|学习笔记|17|0|2022-01-12|
|136|[China-ChallengeHub/ChallengeHub-Baselines](https://github.com/China-ChallengeHub/ChallengeHub-Baselines)|ChallengeHub开源的各大比赛baseline集合|75|0|2021-09-24|
|137|[liangruibupt/aws-is-how](https://github.com/liangruibupt/aws-is-how)|Know How Guide and Hands on Guide for AWS|21|0|2022-01-24|
|138|[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|0|2021-08-16|
|139|[waterDLut/hydrus](https://github.com/waterDLut/hydrus)|水文水资源（Hydrology and Water Resources）方面利用python做模型model、算法algorithm等科学计算工作所需的基础技能树学习|23|0|2021-11-16|
|140|[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 |30|0|2021-08-25|
|141|[bobo0810/PytorchNetHub](https://github.com/bobo0810/PytorchNetHub)|项目注释+论文复现+算法竞赛+Pytorch指北|406|0|2021-12-28|
|142|[xuwening/blog](https://github.com/xuwening/blog)|对过往做做总结|91|0|2021-09-16|
|143|[laisimiao/cs231n-Spring2019-assignment](https://github.com/laisimiao/cs231n-Spring2019-assignment)|This is the all answer for stanford course CS231n spring 2019.|31|0|2021-08-27|
|144|[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|24|0|2022-01-27|
|145|[wwtm/gitpython_examples](https://github.com/wwtm/gitpython_examples)|some interesting python examples|52|0|2021-10-16|
|146|[Valuebai/learn-NLP-luhuibo](https://github.com/Valuebai/learn-NLP-luhuibo)|记录学习NLP之路，一起加油|11|0|2021-09-08|
|147|[jikeruohai/machine-learning-example](https://github.com/jikeruohai/machine-learning-example)|我的同名B站和公众号中用到的视频|14|0|2021-10-21|
|148|[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|69|0|2021-10-13|
|149|[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 )|268|0|2021-11-17|
|150|[fanfansann/fanfan-deep-learning-note](https://github.com/fanfansann/fanfan-deep-learning-note)|《繁凡的深度学习笔记》代码、PDF文件仓库|51|0|2022-01-24|
|151|[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|91|0|2021-09-23|
|152|[TinyHandsome/BookStudy](https://github.com/TinyHandsome/BookStudy)|各本书的学习笔记|11|0|2021-12-09|
|153|[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！ |120|0|2021-12-29|
|154|[lipengyuan1994/Patrick-s-DS-Station](https://github.com/lipengyuan1994/Patrick-s-DS-Station)|The Data Science 🔋Learning Station of Pytrick🌰 （ From Coursera, edX, LinkedIn Learning, etc... and Also contains Books).  I am still updating it.|19|0|2021-09-04|
|155|[hanzhenlei767/NLP_Learn](https://github.com/hanzhenlei767/NLP_Learn)|NLP学习笔记-前沿追踪|16|0|2021-08-25|
|156|[zhangjunhd/reading-notes](https://github.com/zhangjunhd/reading-notes)|张俊的读书笔记|80|0|2022-02-06|
|157|[sangyy/CUDA_Python](https://github.com/sangyy/CUDA_Python)|CUDA Python 科普之夜   手把手教你写GPU加速代码|15|0|2021-08-26|
|158|[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）|305|0|2021-12-06|
|159|[evenchange4/nextjs-tfjs-cnn](https://github.com/evenchange4/nextjs-tfjs-cnn)|🐕 🐈 Classifier using Keras VGG16 transfer learning with kaggle dataset.|11|0|2021-10-18|
|160|[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 : )|100|0|2022-01-22|
|161|[Zhouxiaonnan/machine-learning-notesandcode](https://github.com/Zhouxiaonnan/machine-learning-notesandcode)|机器学习学习笔记和代码|31|0|2022-01-31|

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