forked from GrowingGit/GitHub-Chinese-Top-Charts
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathJupyter-Notebook.md
177 lines (172 loc) · 29.7 KB
/
Jupyter-Notebook.md
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
<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>
# 中文总榜 > 资料类 > Jupyter Notebook
<sub>数据更新: 2022-01-16 / 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|16922|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|16223|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|15940|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。|14385|2021-10-14|
|5|[fastai/fastbook](https://github.com/fastai/fastbook)|The fastai book, published as Jupyter Notebooks|14143|2022-01-07|
|6|[selfteaching/the-craft-of-selfteaching](https://github.com/selfteaching/the-craft-of-selfteaching)|One has no future if one couldn't teach themself.|13046|2022-01-07|
|7|[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).|12270|2021-11-24|
|8|[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.|12158|2021-08-30|
|9|[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。|11004|2021-12-24|
|10|[yidao620c/python3-cookbook](https://github.com/yidao620c/python3-cookbook)|《Python Cookbook》 3rd Edition Translation|9753|2021-08-27|
|11|[apachecn/Interview](https://github.com/apachecn/Interview)|Interview = 简历指南 + LeetCode + Kaggle|7231|2022-01-09|
|12|[Mikoto10032/DeepLearning](https://github.com/Mikoto10032/DeepLearning)|深度学习入门教程, 优秀文章, Deep Learning Tutorial|6910|2021-12-27|
|13|[fengdu78/Data-Science-Notes](https://github.com/fengdu78/Data-Science-Notes)|数据科学的笔记以及资料搜集|6179|2021-08-16|
|14|[xianhu/LearnPython](https://github.com/xianhu/LearnPython)|以撸代码的形式学习Python|6083|2021-11-11|
|15|[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|3638|2021-09-04|
|16|[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|3400|2021-08-31|
|17|[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/|3146|2022-01-13|
|18|[datawhalechina/joyful-pandas](https://github.com/datawhalechina/joyful-pandas)|pandas中文教程|2828|2021-10-05|
|19|[PaddlePaddle/book](https://github.com/PaddlePaddle/book)|Deep Learning 101 with PaddlePaddle （『飞桨』深度学习框架入门教程）|2629|2021-11-12|
|20|[datawhalechina/competition-baseline](https://github.com/datawhalechina/competition-baseline)|数据科学竞赛知识、代码、思路|2580|2021-12-03|
|21|[zlotus/notes-linear-algebra](https://github.com/zlotus/notes-linear-algebra)|线性代数笔记|2428|2021-12-13|
|22|[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。|1883|2022-01-14|
|23|[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......|1512|2021-07-26|
|24|[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|1502|2021-12-20|
|25|[Charmve/computer-vision-in-action](https://github.com/Charmve/computer-vision-in-action)|闭环学习《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|1281|2022-01-11|
|26|[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. ...|1197|2022-01-13|
|27|[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|1154|2022-01-15|
|28|[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。|1001|2021-10-27|
|29|[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。|930|2021-12-02|
|30|[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|885|2021-11-26|
|31|[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）|862|2021-12-10|
|32|[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|716|2022-01-12|
|33|[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》|679|2021-11-03|
|34|[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|672|2021-10-17|
|35|[MorvanZhou/easy-scraping-tutorial](https://github.com/MorvanZhou/easy-scraping-tutorial)|Simple but useful Python web scraping tutorial code. |644|2021-08-18|
|36|[ZhiqingXiao/rl-book](https://github.com/ZhiqingXiao/rl-book)|Source codes for the book "Reinforcement Learning: Theory and Python Implementation"|608|2021-12-12|
|37|[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|607|2021-12-27|
|38|[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）|600|2021-12-17|
|39|[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。|582|2021-12-18|
|40|[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。|558|2021-11-05|
|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|527|2021-09-09|
|42|[openvinotoolkit/openvino_notebooks](https://github.com/openvinotoolkit/openvino_notebooks)|📚 A collection of Jupyter notebooks for learning and experimenting with OpenVINO 👓|505|2022-01-14|
|43|[bobo0810/PytorchNetHub](https://github.com/bobo0810/PytorchNetHub)|项目注释+论文复现+算法竞赛+Pytorch指北|405|2021-12-28|
|44|[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。|404|2021-09-17|
|45|[evanzd/ICLR2021-OpenReviewData](https://github.com/evanzd/ICLR2021-OpenReviewData)|Crawl & visualize ICLR papers and reviews.|399|2021-11-09|
|46|[liuhuanshuo/zaoqi-Python](https://github.com/liuhuanshuo/zaoqi-Python)|公众号：早起Python|301|2021-10-20|
|47|[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）|295|2021-12-06|
|48|[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 )|265|2021-11-17|
|49|[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|248|2022-01-12|
|50|[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/|241|2022-01-07|
|51|[d2l-ai/courses-zh-v2](https://github.com/d2l-ai/courses-zh-v2)|中文版 v2 课程|235|2021-09-14|
|52|[xinychen/latex-cookbook](https://github.com/xinychen/latex-cookbook)|LaTeX论文写作教程 (中文版)|208|2022-01-14|
|53|[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|2022-01-13|
|54|[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|188|2021-10-10|
|55|[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。|179|2021-09-06|
|56|[microsoft/AIforEarthDataSets](https://github.com/microsoft/AIforEarthDataSets)|Notebooks and documentation for AI-for-Earth-managed datasets on Azure|170|2022-01-07|
|57|[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|167|2021-12-08|
|58|[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|2021-12-29|
|59|[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。|166|2021-08-19|
|60|[simbafl/Data-analysis](https://github.com/simbafl/Data-analysis)|主要是爬虫与数据分析项目总结，外加建模与机器学习，模型的评估。|155|2022-01-02|
|61|[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|155|2021-09-17|
|62|[sijichun/MathStatsCode](https://github.com/sijichun/MathStatsCode)|Codes for my mathematical statistics course|150|2021-12-27|
|63|[liuhuanshuo/Pandas_Advanced_Exercise](https://github.com/liuhuanshuo/Pandas_Advanced_Exercise)|Pandas进阶修炼300题|149|2021-09-22|
|64|[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|126|2021-11-29|
|65|[datawhalechina/machine-learning-toy-code](https://github.com/datawhalechina/machine-learning-toy-code)|《机器学习》（西瓜书）代码实战|124|2022-01-04|
|66|[beiciliang/intro2musictech](https://github.com/beiciliang/intro2musictech)|公众号“无痛入门音乐科技”开源代码|123|2021-10-31|
|67|[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！ |112|2021-12-29|
|68|[0809zheng/CS231n-assignment2019](https://github.com/0809zheng/CS231n-assignment2019)|CS231n 2019年春季学期课程作业|97|2022-01-13|
|69|[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 : )|95|2022-01-12|
|70|[Divsigma/2020-cs213n](https://github.com/Divsigma/2020-cs213n)|一些公开课的笔记及作业|92|2021-11-13|
|71|[xuwening/blog](https://github.com/xuwening/blog)|对过往做做总结|91|2021-09-16|
|72|[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|90|2021-09-23|
|73|[batermj/data_sciences_campaign](https://github.com/batermj/data_sciences_campaign)|【数据科学家系列课程】|85|2022-01-15|
|74|[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|82|2022-01-07|
|75|[China-ChallengeHub/ChallengeHub-Baselines](https://github.com/China-ChallengeHub/ChallengeHub-Baselines)|ChallengeHub开源的各大比赛baseline集合|76|2021-09-24|
|76|[neolee/pilot-student](https://github.com/neolee/pilot-student)|“进入编程世界的第一课” 的学习用书|76|2021-12-23|
|77|[zhangjunhd/reading-notes](https://github.com/zhangjunhd/reading-notes)|张俊的读书笔记|71|2022-01-13|
|78|[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|70|2021-12-23|
|79|[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。|68|2021-10-21|
|80|[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|64|2021-10-13|
|81|[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|
|82|[afunTW/Python-Crawling-Tutorial](https://github.com/afunTW/Python-Crawling-Tutorial)|Python crawling tutorial|61|2021-12-13|
|83|[newaetech/chipwhisperer-jupyter](https://github.com/newaetech/chipwhisperer-jupyter)|Interactive ChipWhisperer tutorials using Jupyter notebooks.|57|2021-12-08|
|84|[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|2022-01-13|
|85|[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|54|2021-12-28|
|86|[skywateryang/timeseries101](https://github.com/skywateryang/timeseries101)|本教程独立网站已上线|53|2021-12-28|
|87|[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|52|2021-07-29|
|88|[wwtm/gitpython_examples](https://github.com/wwtm/gitpython_examples)|some interesting python examples|52|2021-10-16|
|89|[zhangjx831/Data-Science-Notes](https://github.com/zhangjx831/Data-Science-Notes)|数据科学与机器学习炼成笔记|51|2021-12-29|
|90|[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|2021-12-17|
|91|[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|2022-01-13|
|92|[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|
|93|[ssssww0905/-PyTorch-](https://github.com/ssssww0905/-PyTorch-)|【PyTorch】手把手教你跑通第一个神经网络|50|2022-01-03|
|94|[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.|50|2021-12-11|
|95|[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|48|2021-10-16|
|96|[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。|48|2021-10-27|
|97|[lululxvi/tutorials](https://github.com/lululxvi/tutorials)|Tutorials on deep learning, Python, and dissipative particle dynamics|47|2021-12-14|
|98|[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）|45|2022-01-10|
|99|[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|2021-12-11|
|100|[SocratesAcademy/css](https://github.com/SocratesAcademy/css)|《计算社会科学》课程|44|2021-09-11|
|101|[MachineLP/Spark-](https://github.com/MachineLP/Spark-)|Spark学习笔记|42|2021-12-09|
|102|[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|2021-11-05|
|103|[johnjim0816/rl-tutorials](https://github.com/johnjim0816/rl-tutorials)|basic algorithms of reinforcement learning|39|2021-12-29|
|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|39|2022-01-13|
|105|[LaoGong-zp/Transformer](https://github.com/LaoGong-zp/Transformer)| Learning materials of Transformer, including my code, XMind, PDF and so on|38|2021-09-28|
|106|[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|38|2021-12-29|
|107|[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|37|2021-12-05|
|108|[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|37|2021-08-08|
|109|[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|37|2021-12-27|
|110|[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|2022-01-09|
|111|[IBBD/IBBD.github.io](https://github.com/IBBD/IBBD.github.io)|IBBD技术博客|35|2021-07-17|
|112|[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|2021-08-25|
|113|[jcchan23/CoMPT](https://github.com/jcchan23/CoMPT)|Code of our IJCAI2021 paper: "Learning Attributed Graph Representation with Communicative Message Passing Transformer"|33|2021-09-08|
|114|[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。|33|2021-08-16|
|115|[mindspore-ai/course](https://github.com/mindspore-ai/course)|MindSpore course|33|2021-11-03|
|116|[laisimiao/cs231n-Spring2019-assignment](https://github.com/laisimiao/cs231n-Spring2019-assignment)|This is the all answer for stanford course CS231n spring 2019.|31|2021-08-27|
|117|[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|2021-08-25|
|118|[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|2021-08-25|
|119|[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。|27|2021-11-20|
|120|[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|2022-01-12|
|121|[tsaac/Python](https://github.com/tsaac/Python)|YINUXY的python脚本分享|23|2021-09-20|
|122|[eagle-dai/OptimizingSoftwareInCpp](https://github.com/eagle-dai/OptimizingSoftwareInCpp)|Optimizing Software In C++ 非正式中文翻译|23|2022-01-12|
|123|[Anjin-Liu/Openset_Learning_AOSR](https://github.com/Anjin-Liu/Openset_Learning_AOSR)|Source code for ICML2021 Paper - Learning Bounds for Open-set Learning|22|2021-07-17|
|124|[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|22|2021-11-16|
|125|[liangruibupt/aws-is-how](https://github.com/liangruibupt/aws-is-how)|Know How Guide and Hands on Guide for AWS|21|2022-01-13|
|126|[hzcforever/Something](https://github.com/hzcforever/Something)|面试知识点 + 笔试刷题总结。|21|2021-09-15|
|127|[dmarx/anthology-of-modern-ml](https://github.com/dmarx/anthology-of-modern-ml)|Collection of important articles to be treated as a textbook|20|2022-01-14|
|128|[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|19|2022-01-13|
|129|[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|2021-10-21|
|130|[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|2021-09-04|
|131|[JULIELab/MEmoLon](https://github.com/JULIELab/MEmoLon)|Repository for our ACL 2020 paper "Learning and Evaluating Emotion Lexicons for 91 Languages"|18|2021-08-23|
|132|[fry404006308/fry_course_materials](https://github.com/fry404006308/fry_course_materials)|范仁义录播课资料|18|2022-01-14|
|133|[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|2022-01-09|
|134|[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|2021-10-15|
|135|[zzy99/competition-solutions](https://github.com/zzy99/competition-solutions)|我的数据竞赛方案总结|17|2021-11-16|
|136|[xiaomeng79/learning_notes](https://github.com/xiaomeng79/learning_notes)|学习笔记|17|2022-01-12|
|137|[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|16|2021-09-17|
|138|[hanzhenlei767/NLP_Learn](https://github.com/hanzhenlei767/NLP_Learn)|NLP学习笔记-前沿追踪|16|2021-08-25|
|139|[fire717/Python-Toolkit](https://github.com/fire717/Python-Toolkit)|轮子/ 常用库/ 书籍笔记/ 小程序|16|2022-01-14|
|140|[whyAndBetter/python_grammar](https://github.com/whyAndBetter/python_grammar)|Python的基础语法学习|15|2022-01-09|
|141|[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。|15|2022-01-02|
|142|[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）|15|2021-08-25|
|143|[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|2021-10-21|
|144|[Relph1119/Pytorch-Camp](https://github.com/Relph1119/Pytorch-Camp)|深度之眼《Pytorch框架训练营》|14|2021-10-12|
|145|[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|13|2021-10-02|
|146|[rwepa/DataDemo](https://github.com/rwepa/DataDemo)|提供資料集與範例分享.|13|2021-11-11|
|147|[Hourout/tensorview](https://github.com/Hourout/tensorview)|Dynamic visualization training service in Jupyter Notebook for Keras, tf.keras and others.|13|2021-07-22|
|148|[NjtechCVLab/Level_1](https://github.com/NjtechCVLab/Level_1)|入门资料|12|2021-11-29|
|149|[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|2021-09-25|
|150|[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|12|2021-09-08|
|151|[SocratesAcademy/ccbook](https://github.com/SocratesAcademy/ccbook)|Elements of Computational Communication 《计算传播基础》|12|2021-09-27|
|152|[hanx316/Tech-Notes](https://github.com/hanx316/Tech-Notes)|📒 技术学习笔记，好记性不如 Markdown|12|2021-07-24|
|153|[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|2021-09-15|
|154|[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|11|2021-08-26|
|155|[BrikerMan/tf2-101](https://github.com/BrikerMan/tf2-101)|Repository for Book 《TensorFlow 2.0 入门实践》|11|2021-10-28|
|156|[Mazeqi/PaperNote](https://github.com/Mazeqi/PaperNote)|阅读论文的一些笔记|11|2021-12-09|
|157|[evenchange4/nextjs-tfjs-cnn](https://github.com/evenchange4/nextjs-tfjs-cnn)|🐕 🐈 Classifier using Keras VGG16 transfer learning with kaggle dataset.|11|2021-10-18|
|158|[Valuebai/learn-NLP-luhuibo](https://github.com/Valuebai/learn-NLP-luhuibo)|记录学习NLP之路，一起加油|11|2021-09-08|
|159|[TinyHandsome/BookStudy](https://github.com/TinyHandsome/BookStudy)|各本书的学习笔记|11|2021-12-09|
|160|[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|2021-09-23|
|161|[wanghao15536870732/StudyNotes](https://github.com/wanghao15536870732/StudyNotes)|📖 学习笔记|10|2021-11-08|
<div align="center">
<p><sub>↓ -- 感谢读者 -- ↓</sub></p>
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！
</div>
<br/>
<div align="center"><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></div>