返回目录 • 问题反馈 # 中文总榜 > 资料类 > Jupyter Notebook 数据更新: 2022-04-10   /   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 |#|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|17929|2022-04-06| |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|16911|2022-04-03| |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|16336|2022-03-25| |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。|14792|2021-10-14| |5|[fastai/fastbook](https://github.com/fastai/fastbook)|The fastai book, published as Jupyter Notebooks|14643|2022-04-06| |6|[selfteaching/the-craft-of-selfteaching](https://github.com/selfteaching/the-craft-of-selfteaching)|One has no future if one couldn't teach themself.|13270|2022-04-01| |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).|12537|2021-11-24| |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。|11620|2022-04-01| |9|[yidao620c/python3-cookbook](https://github.com/yidao620c/python3-cookbook)|《Python Cookbook》 3rd Edition Translation|9931|2022-02-01| |10|[apachecn/Interview](https://github.com/apachecn/Interview)|Interview = 简历指南 + 算法题 + 八股文 + 源码分析|7422|2022-03-12| |11|[Mikoto10032/DeepLearning](https://github.com/Mikoto10032/DeepLearning)|深度学习入门教程, 优秀文章, Deep Learning Tutorial|7358|2021-12-27| |12|[xianhu/LearnPython](https://github.com/xianhu/LearnPython)|以撸代码的形式学习Python|6211|2021-11-11| |13|[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/|4372|2022-04-04| |14|[datawhalechina/competition-baseline](https://github.com/datawhalechina/competition-baseline)|数据科学竞赛知识、代码、思路|2759|2022-03-29| |15|[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|2021-11-12| |16|[zlotus/notes-linear-algebra](https://github.com/zlotus/notes-linear-algebra)|线性代数笔记|2488|2021-12-13| |17|[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|2040|2022-04-05| |18|[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。|1944|2022-01-14| |19|[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|1402|2022-03-31| |20|[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|1354|2022-03-25| |21|[gedeck/practical-statistics-for-data-scientists](https://github.com/gedeck/practical-statistics-for-data-scientists)|Code repository for O'Reilly book|1231|2022-03-11| |22|[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. ...|1223|2022-03-11| |23|[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、ML、DL、NLP-BERT、竞赛。含大量注释及数据集，力求每一位能看懂并复现。|1119|2021-10-27| |24|[luwill/Machine_Learning_Code_Implementation](https://github.com/luwill/Machine_Learning_Code_Implementation)|Mathematical derivation and pure Python code implementation of machine learning algorithms.|1079|2022-04-06| |25|[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。|1028|2022-03-16| |26|[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）|978|2022-02-12| |27|[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|898|2022-03-08| |28|[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|883|2022-01-19| |29|[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|794|2022-03-25| |30|[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》|736|2021-11-03| |31|[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|724|2022-03-12| |32|[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|719|2021-10-17| |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）|636|2021-12-17| |34|[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。|627|2022-03-01| |35|[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。|607|2022-02-23| |36|[openvinotoolkit/openvino_notebooks](https://github.com/openvinotoolkit/openvino_notebooks)|📚 A collection of Jupyter notebooks for learning and experimenting with OpenVINO 👓|598|2022-04-09| |37|[bobo0810/PytorchNetHub](https://github.com/bobo0810/PytorchNetHub)|项目注释+论文复现+算法竞赛+Pytorch指北|422|2022-03-24| |38|[evanzd/ICLR2021-OpenReviewData](https://github.com/evanzd/ICLR2021-OpenReviewData)|Crawl & visualize ICLR papers and reviews.|412|2021-11-09| |39|[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）|384|2022-03-22| |40|[LiuChuang0059/Complex-Network](https://github.com/LiuChuang0059/Complex-Network)|复杂网络研究资源整理和基础知识学习|336|2022-02-27| |41|[xinychen/latex-cookbook](https://github.com/xinychen/latex-cookbook)|LaTeX论文写作教程 (中文版)|321|2022-04-06| |42|[liuhuanshuo/zaoqi-Python](https://github.com/liuhuanshuo/zaoqi-Python)|公众号：早起Python|321|2022-02-07| |43|[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 )|289|2021-11-17| |44|[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/|269|2022-01-07| |45|[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|256|2022-03-05| |46|[virginiakm1988/ML2022-Spring](https://github.com/virginiakm1988/ML2022-Spring)|**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2022 Spring|245|2022-04-03| |47|[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|202|2021-12-08| |48|[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|190|2021-10-10| |49|[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|2022-04-06| |50|[microsoft/AIforEarthDataSets](https://github.com/microsoft/AIforEarthDataSets)|Notebooks and documentation for AI-for-Earth-managed datasets on Azure|183|2022-03-21| |51|[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！ |174|2022-04-08| |52|[GiantPandaCV/yolov3-point](https://github.com/GiantPandaCV/yolov3-point)|从零开始学习YOLOv3代码|172|2022-03-14| |53|[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...）|169|2022-03-14| |54|[sijichun/MathStatsCode](https://github.com/sijichun/MathStatsCode)|Codes for my mathematical statistics course|153|2021-12-27| |55|[datawhalechina/machine-learning-toy-code](https://github.com/datawhalechina/machine-learning-toy-code)|《机器学习》（西瓜书）代码实战|148|2022-01-04| |56|[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|145|2021-11-29| |57|[beiciliang/intro2musictech](https://github.com/beiciliang/intro2musictech)|公众号“无痛入门音乐科技”开源代码|130|2021-10-31| |58|[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|118|2022-03-06| |59|[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 : )|112|2022-03-07| |60|[zhangjunhd/reading-notes](https://github.com/zhangjunhd/reading-notes)|张俊的读书笔记|112|2022-04-09| |61|[0809zheng/CS231n-assignment2019](https://github.com/0809zheng/CS231n-assignment2019)|CS231n 2019年春季学期课程作业|101|2022-04-06| |62|[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。|94|2022-03-21| |63|[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|90|2022-01-07| |64|[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）|89|2022-03-21| |65|[batermj/data_sciences_campaign](https://github.com/batermj/data_sciences_campaign)|【数据科学家系列课程】|86|2022-04-09| |66|[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|82|2021-12-23| |67|[neolee/pilot-student](https://github.com/neolee/pilot-student)|“进入编程世界的第一课” 的学习用书|82|2022-01-28| |68|[China-ChallengeHub/ChallengeHub-Baselines](https://github.com/China-ChallengeHub/ChallengeHub-Baselines)|ChallengeHub开源的各大比赛baseline集合|77|2022-03-12| |69|[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|74|2022-02-15| |70|[skywateryang/timeseries101](https://github.com/skywateryang/timeseries101)|本教程独立网站已上线|67|2021-12-28| |71|[newaetech/chipwhisperer-jupyter](https://github.com/newaetech/chipwhisperer-jupyter)|Interactive ChipWhisperer tutorials using Jupyter notebooks.|67|2022-04-07| |72|[lululxvi/tutorials](https://github.com/lululxvi/tutorials)|Tutorials on deep learning, Python, and dissipative particle dynamics|66|2021-12-14| |73|[zhangjx831/Data-Science-Notes](https://github.com/zhangjx831/Data-Science-Notes)|数据科学与机器学习炼成笔记|64|2022-03-08| |74|[ssssww0905/-PyTorch-](https://github.com/ssssww0905/-PyTorch-)|【PyTorch】手把手教你跑通第一个神经网络|63|2022-01-03| |75|[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.|61|2022-03-24| |76|[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。|61|2022-03-11| |77|[afunTW/Python-Crawling-Tutorial](https://github.com/afunTW/Python-Crawling-Tutorial)|Python crawling tutorial|61|2022-01-26| |78|[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|60|2021-12-28| |79|[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|60|2021-10-16| |80|[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）|56|2022-03-12| |81|[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|53|2021-12-17| |82|[wwtm/gitpython_examples](https://github.com/wwtm/gitpython_examples)|some interesting python examples|51|2021-10-16| |83|[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|2022-02-27| |84|[SocratesAcademy/css](https://github.com/SocratesAcademy/css)|《计算社会科学》课程|50|2022-02-06| |85|[km1994/GCN_study](https://github.com/km1994/GCN_study)|GCN 入门学习教程|49|2022-01-19| |86|[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|2022-01-21| |87|[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|48|2021-12-27| |88|[lqhou/TensorFlow2.0-Book](https://github.com/lqhou/TensorFlow2.0-Book)|《TensorFlow从零开始学》配书代码和资源|47|2022-03-07| |89|[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:|46|2021-12-11| |90|[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|43|2022-03-08| |91|[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|42|2021-12-05| |92|[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)|42|2021-11-05| |93|[MachineLP/Spark-](https://github.com/MachineLP/Spark-)|Spark学习笔记|42|2022-02-11| |94|[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|41|2022-04-08| |95|[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|40|2022-02-10| |96|[johnjim0816/rl-tutorials](https://github.com/johnjim0816/rl-tutorials)|basic algorithms of reinforcement learning|39|2021-12-29| |97|[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|2022-03-29| |98|[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|2022-04-06| |99|[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. |38|2022-03-10| |100|[datawhalechina/hands-dirty-nlp](https://github.com/datawhalechina/hands-dirty-nlp)|本课程面对具有一定机器学习基础，但尚未入门的NLPer或经验尚浅的NLPer，尽力避免陷入繁琐枯燥的公式讲解中，力求用代码展示每个模型背后的设计思想，同时也会带大家梳理每个模块下的技术演变，做到既知树木也知森林。|37|2022-02-19| |101|[Zhouxiaonnan/machine-learning-notesandcode](https://github.com/Zhouxiaonnan/machine-learning-notesandcode)|机器学习学习笔记和代码|36|2022-03-02| |102|[jcchan23/CoMPT](https://github.com/jcchan23/CoMPT)|Code of our IJCAI2021 paper: "Learning Attributed Graph Representation with Communicative Message Passing Transformer"|34|2022-03-19| |103|[mindspore-ai/course](https://github.com/mindspore-ai/course)|MindSpore course|33|2022-02-27| |104|[zhiyu1998/Computer-Science-Learn-Notes](https://github.com/zhiyu1998/Computer-Science-Learn-Notes)|CS（Computer Science）生涯学习/读书笔记，包含：Java八股文、JVM、JUC、前端、Spring系列、Python、Golang、深度学习、数据结构和算法等|32|2022-04-07| |105|[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|2022-02-10| |106|[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。|29|2021-11-20| |107|[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 ；|29|2022-03-27| |108|[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.|29|2022-03-18| |109|[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|2022-04-06| |110|[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）|28|2022-02-26| |111|[SocratesAcademy/ccbook](https://github.com/SocratesAcademy/ccbook)|Elements of Computational Communication 《计算传播基础》|27|2022-02-26| |112|[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|26|2021-11-16| |113|[zyth0s/SciAlgs.jl](https://github.com/zyth0s/SciAlgs.jl)|Fundamental scientific algorithms in Julia|24|2022-03-31| |114|[WayneDW/Contour-Stochastic-Gradient-Langevin-Dynamics](https://github.com/WayneDW/Contour-Stochastic-Gradient-Langevin-Dynamics)|An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)|23|2022-03-14| |115|[HuangCongQing/CS231n_Spring_2019](https://github.com/HuangCongQing/CS231n_Spring_2019)|CS231n_Spring（2019年秋季）计算机视觉课程|23|2022-01-09| |116|[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|23|2021-10-21| |117|[eagle-dai/OptimizingSoftwareInCpp](https://github.com/eagle-dai/OptimizingSoftwareInCpp)|Optimizing Software In C++ 非正式中文翻译|23|2022-01-17| |118|[liangruibupt/aws-is-how](https://github.com/liangruibupt/aws-is-how)|Know How Guide and Hands on Guide for AWS|22|2022-04-07| |119|[dmarx/anthology-of-modern-ml](https://github.com/dmarx/anthology-of-modern-ml)|Collection of important articles to be treated as a textbook|20|2022-02-16| |120|[JULIELab/MEmoLon](https://github.com/JULIELab/MEmoLon)|Repository for our ACL 2020 paper "Learning and Evaluating Emotion Lexicons for 91 Languages"|20|2022-04-06| |121|[wybert/open-wuhan-ncov-illness-data](https://github.com/wybert/open-wuhan-ncov-illness-data)|这个项目有关有关 武汉肺炎 2019-ncov的相关病例数据的分享。从gitlab迁移过来。发布页这里|20|2022-03-30| |122|[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。|19|2022-02-02| |123|[zzy99/competition-solutions](https://github.com/zzy99/competition-solutions)|我的数据竞赛方案总结|19|2021-11-16| |124|[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|19|2022-04-05| |125|[chinobing/QuantInvest](https://github.com/chinobing/QuantInvest)|cnvar.cn及个人微信公众号【QuantInvest】里面提及的编程代码, 对股票各种研究和折腾分析A股市场的各种现象和投资机会，涉及编程、股票模型、分析研究、杂谈等，代码是python，以jupyter notebook展示。|19|2022-03-16| |126|[hanzhenlei767/NLP_Learn](https://github.com/hanzhenlei767/NLP_Learn)|NLP学习笔记-前沿追踪|19|2022-02-10| |127|[AccumulateMore/CPlusPlus](https://github.com/AccumulateMore/CPlusPlus)|最细致的 C++ 笔记|18|2022-04-06| |128|[xiaomeng79/learning_notes](https://github.com/xiaomeng79/learning_notes)|学习笔记|18|2022-04-02| |129|[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| |130|[raymondlo84/openvino-paddlepaddle-demo](https://github.com/raymondlo84/openvino-paddlepaddle-demo)|This repository provides examples of PaddlePaddle and OpenVINO integration. |17|2022-03-15| |131|[BrikerMan/tf2-101](https://github.com/BrikerMan/tf2-101)|Repository for Book 《TensorFlow 2.0 入门实践》|17|2021-10-28| |132|[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|17|2022-03-12| |133|[fire717/Python-Toolkit](https://github.com/fire717/Python-Toolkit)|轮子/ 常用库/ 书籍笔记/ 小程序|17|2022-03-03| |134|[Alex-Shen1121/SZU_Learning_Resource](https://github.com/Alex-Shen1121/SZU_Learning_Resource)|深圳大学CS本科 课程资源共享|16|2022-03-31| |135|[PouringRain/blog_code](https://github.com/PouringRain/blog_code)|存放知乎，博客发表文章中的代码|15|2021-10-17| |136|[whyAndBetter/python_grammar](https://github.com/whyAndBetter/python_grammar)|Python的基础语法学习|15|2022-01-09| |137|[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|15|2022-01-13| |138|[NjtechCVLab/Level_1](https://github.com/NjtechCVLab/Level_1)|入门资料|15|2022-03-31| |139|[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|2022-04-09| |140|[Relph1119/Pytorch-Camp](https://github.com/Relph1119/Pytorch-Camp)|深度之眼《Pytorch框架训练营》|15|2022-04-06| |141|[lyj555/SelfLearning](https://github.com/lyj555/SelfLearning)|该项目主要是自学过程中对于一些知识点的整理，项目整体分为四部分，分别是算法、工程、工具和数学知识。算法部分主要是常用的机器学习（LR、SVM、树模型、XGBoost、LightGBM和CatBoost等）和深度学习算法（NLP和CV以及一些基础知识），工程部分主要是spark和hive|15|2022-03-25| |142|[zui0711/Z-Lab](https://github.com/zui0711/Z-Lab)|Z Lab数据实验室开源代码汇总|14|2022-04-09| |143|[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|2022-04-06| |144|[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|13|2022-03-10| |145|[rwepa/DataDemo](https://github.com/rwepa/DataDemo)|提供資料集與範例分享.|13|2022-03-26| |146|[IKMLab/course_material](https://github.com/IKMLab/course_material)|上課教材的大集合！！！|13|2022-03-29| |147|[Hourout/tensorview](https://github.com/Hourout/tensorview)|Dynamic visualization training service in Jupyter Notebook for Keras, tf.keras and others.|13|2022-03-22| |148|[Mazeqi/PaperNote](https://github.com/Mazeqi/PaperNote)|阅读论文的一些笔记|11|2021-12-09| |149|[evenchange4/nextjs-tfjs-cnn](https://github.com/evenchange4/nextjs-tfjs-cnn)|🐕 🐈 Classifier using Keras VGG16 transfer learning with kaggle dataset.|11|2021-10-18| |150|[TinyHandsome/BookStudy](https://github.com/TinyHandsome/BookStudy)|各本书的学习笔记|11|2021-12-09| |151|[wanghao15536870732/StudyNotes](https://github.com/wanghao15536870732/StudyNotes)|📖 学习笔记|10|2021-11-08|

↓ -- 感谢读者 -- ↓

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！

返回目录 • 问题反馈