117 lines
20 KiB
Java
117 lines
20 KiB
Java
<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>
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# 中文增速榜 > 资料类 > Jupyter Notebook
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<sub>数据更新: 2021-12-22 / 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|14014|21|2021-12-07|
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|2|[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。|14238|14|2021-10-14|
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|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|15827|14|2021-10-25|
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|4|[MLEveryday/100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|100-Days-Of-ML-Code中文版|16833|14|2021-08-11|
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|5|[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.|12112|13|2021-08-30|
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|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。|10847|12|2021-06-26|
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|7|[fengdu78/Data-Science-Notes](https://github.com/fengdu78/Data-Science-Notes)|数据科学的笔记以及资料搜集|6087|7|2021-08-16|
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|8|[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/|3012|6|2021-12-21|
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|9|[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|1238|5|2021-12-14|
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|10|[apachecn/Interview](https://github.com/apachecn/Interview)|Interview = 简历指南 + LeetCode + Kaggle|7208|5|2021-11-07|
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|11|[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|11432|5|2021-07-30|
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|12|[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|16107|5|2021-12-16|
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|13|[Mikoto10032/DeepLearning](https://github.com/Mikoto10032/DeepLearning)|深度学习入门教程, 优秀文章, Deep Learning Tutorial|6790|5|2021-10-21|
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|14|[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|1353|5|2021-12-20|
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|15|[yidao620c/python3-cookbook](https://github.com/yidao620c/python3-cookbook)|《Python Cookbook》 3rd Edition Translation|9696|4|2021-08-27|
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|16|[datawhalechina/joyful-pandas](https://github.com/datawhalechina/joyful-pandas)|pandas中文教程|2791|4|2021-10-05|
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|17|[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|3381|3|2021-08-31|
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|18|[xianhu/LearnPython](https://github.com/xianhu/LearnPython)|以撸代码的形式学习Python|6043|3|2021-11-11|
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|19|[datawhalechina/competition-baseline](https://github.com/datawhalechina/competition-baseline)|数据科学竞赛知识、代码、思路|2555|3|2021-12-03|
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|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|3617|3|2021-09-04|
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|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）|795|3|2021-12-10|
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|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|2|2021-07-26|
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|23|[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. |931|2|2021-12-20|
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|24|[openvinotoolkit/openvino_notebooks](https://github.com/openvinotoolkit/openvino_notebooks)|📚 A collection of Jupyter notebooks for learning and experimenting with OpenVINO 👓|484|2|2021-12-21|
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|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。|902|2|2021-12-02|
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|26|[liuhuanshuo/Pandas_Advanced_Exercise](https://github.com/liuhuanshuo/Pandas_Advanced_Exercise)|Pandas进阶修炼300题|140|2|2021-09-22|
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|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。|980|2|2021-10-27|
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|28|[datamonday/Time-Series-Analysis-Tutorial](https://github.com/datamonday/Time-Series-Analysis-Tutorial)|时间序列分析教程|188|1|2021-06-01|
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|29|[xianghuisun/Chinese_KGQA](https://github.com/xianghuisun/Chinese_KGQA)|该仓库目的是实现基于知识图谱的中文问答系统|14|1|2021-12-20|
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|30|[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|1|2021-12-18|
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|31|[ssssww0905/-PyTorch-](https://github.com/ssssww0905/-PyTorch-)|【PyTorch】手把手教你跑通第一个神经网络|39|1|2021-12-21|
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|32|[microsoft/AIforEarthDataSets](https://github.com/microsoft/AIforEarthDataSets)|Notebooks and documentation for AI-for-Earth-managed datasets on Azure|165|1|2021-12-16|
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|33|[wolfparticle/machineLearningDeepLearning](https://github.com/wolfparticle/machineLearningDeepLearning)|李宏毅2021机器学习深度学习笔记PPT作业|338|1|2021-06-14|
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|34|[xinychen/latex-cookbook](https://github.com/xinychen/latex-cookbook)|LaTeX论文写作教程 (中文版)|160|1|2021-12-11|
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|35|[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|1|2021-08-09|
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|36|[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|1|2021-11-26|
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|37|[fly51fly/Practical_Python_Programming](https://github.com/fly51fly/Practical_Python_Programming)|北邮《Python编程与实践》课程资料|641|1|2021-06-09|
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|38|[zlotus/notes-linear-algebra](https://github.com/zlotus/notes-linear-algebra)|线性代数笔记|2400|1|2021-12-13|
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|39|[ZhiqingXiao/rl-book](https://github.com/ZhiqingXiao/rl-book)|Source codes for the book "Reinforcement Learning: Theory and Python Implementation"|603|1|2021-12-12|
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|40|[PaddlePaddle/book](https://github.com/PaddlePaddle/book)|Deep Learning 101 with PaddlePaddle （『飞桨』深度学习框架入门教程）|2622|1|2021-11-12|
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|41|[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|1104|1|2021-12-13|
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|42|[ga642381/ML2021-Spring](https://github.com/ga642381/ML2021-Spring)|**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2021 Spring|414|1|2021-06-18|
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|43|[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》|645|1|2021-11-03|
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|44|[d2l-ai/courses-zh-v2](https://github.com/d2l-ai/courses-zh-v2)|中文版 v2 课程|224|1|2021-09-14|
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|45|[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）|582|1|2021-12-17|
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|46|[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|1|2021-10-30|
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|47|[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. ...|1190|1|2021-09-08|
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|48|[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|694|1|2021-12-05|
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|49|[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|1|2021-10-17|
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|50|[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|577|1|2021-12-17|
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|51|[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|87|1|2021-09-23|
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|52|[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。|1856|1|2021-12-21|
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|53|[datawhalechina/machine-learning-toy-code](https://github.com/datawhalechina/machine-learning-toy-code)|《机器学习》（西瓜书）代码实战|99|1|2021-12-17|
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|54|[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|498|1|2021-09-09|
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|55|[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。|390|1|2021-09-17|
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|56|[evanzd/ICLR2021-OpenReviewData](https://github.com/evanzd/ICLR2021-OpenReviewData)|Crawl & visualize ICLR papers and reviews.|392|1|2021-11-09|
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|57|[datawhalechina/wow-plotly](https://github.com/datawhalechina/wow-plotly)|高级可视化神器plotly的学习|16|0|2021-07-04|
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|58|[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|0|2021-10-27|
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|59|[zzy99/competition-solutions](https://github.com/zzy99/competition-solutions)|我的数据竞赛方案总结|17|0|2021-11-16|
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|60|[fry404006308/fry_course_materials](https://github.com/fry404006308/fry_course_materials)|范仁义录播课资料|17|0|2021-11-03|
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|61|[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|0|2021-10-02|
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|62|[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。|547|0|2021-11-05|
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|63|[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.|45|0|2021-12-11|
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|64|[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|
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|65|[sijichun/MathStatsCode](https://github.com/sijichun/MathStatsCode)|Codes for my mathematical statistics course|148|0|2021-10-25|
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|66|[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|
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|67|[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。|172|0|2021-09-06|
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|68|[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|33|0|2021-08-25|
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|69|[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|0|2021-12-11|
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|70|[Mazeqi/PaperNote](https://github.com/Mazeqi/PaperNote)|阅读论文的一些笔记|11|0|2021-12-09|
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|71|[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|
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|72|[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|33|0|2021-12-05|
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|73|[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|0|2021-10-16|
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|74|[BrikerMan/tf2-101](https://github.com/BrikerMan/tf2-101)|Repository for Book 《TensorFlow 2.0 入门实践》|11|0|2021-10-28|
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|75|[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|0|2021-08-19|
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|76|[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|0|2021-09-08|
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|77|[ljyslyc/Book-KnowledgeGraph-Recommendation](https://github.com/ljyslyc/Book-KnowledgeGraph-Recommendation)|书籍知识图谱推荐系统|25|0|2021-07-20|
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|78|[chinapnr/python_study](https://github.com/chinapnr/python_study)|python 入门培训教材，实用、快速、清晰|42|0|2021-06-24|
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|79|[xhnae86/100python-](https://github.com/xhnae86/100python-)|Python 100天练习进阶|19|0|2021-06-01|
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|80|[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。|31|0|2021-08-16|
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|81|[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|2021-12-14|
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|82|[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|37|0|2021-12-09|
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|83|[JULIELab/MEmoLon](https://github.com/JULIELab/MEmoLon)|Repository for our ACL 2020 paper "Learning and Evaluating Emotion Lexicons for 91 Languages"|17|0|2021-08-23|
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|84|[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|31|0|2021-12-14|
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|85|[NjtechCVLab/Level_1](https://github.com/NjtechCVLab/Level_1)|入门资料|12|0|2021-11-29|
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|86|[SocratesAcademy/css](https://github.com/SocratesAcademy/css)|《计算社会科学》课程|43|0|2021-09-11|
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|87|[Global-Policy-Lab/gpl-covid](https://github.com/Global-Policy-Lab/gpl-covid)|Repo for code and small datasets related to Global Policy Lab's COVID-19 policy analysis. Read and share the acompanying article here:|11|0|2021-07-09|
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|88|[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|2021-09-08|
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|89|[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|0|2021-06-07|
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|90|[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）|32|0|2021-12-18|
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|91|[wanghao15536870732/StudyNotes](https://github.com/wanghao15536870732/StudyNotes)|📖 学习笔记|10|0|2021-11-08|
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|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)|38|0|2021-11-05|
|
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|93|[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|0|2021-08-18|
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|94|[fire717/Python-Toolkit](https://github.com/fire717/Python-Toolkit)|轮子/ 常用库/ 书籍笔记/ 小程序|16|0|2021-12-06|
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|95|[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|
|
||
|96|[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|0|2021-10-10|
|
||
|97|[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|0|2021-11-29|
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|98|[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|50|0|2021-12-17|
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|99|[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|0|2021-12-10|
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|100|[hzcforever/Something](https://github.com/hzcforever/Something)|面试知识点 + 笔试刷题总结。|21|0|2021-09-15|
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<div align="center">
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<p><sub>↓ -- 感谢读者 -- ↓</sub></p>
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榜单持续<a href="/content/docs/milestone.md">更新</a>，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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</div>
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