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<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 > 软件类 > Jupyter Notebook
<sub>数据更新: 2022-03-08&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>
<sub>数据更新: 2022-03-09&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|Updated|
|:-|:-|:-|:-|:-|
|1|[MorvanZhou/PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial)|Build your neural network easy and fast, 莫烦Python中文教学|6617|2022-01-20|
|2|[ljpzzz/machinelearning](https://github.com/ljpzzz/machinelearning)|My blogs and code for machine learning. http://cnblogs.com/pinard|6248|2021-10-01|
|3|[roboticcam/machine-learning-notes](https://github.com/roboticcam/machine-learning-notes)|My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接|5671|2022-03-06|
|4|[cleverhans-lab/cleverhans](https://github.com/cleverhans-lab/cleverhans)|An adversarial example library for constructing attacks, building defenses, and benchmarking both|5423|2022-01-23|
|5|[NVIDIA/NeMo](https://github.com/NVIDIA/NeMo)|NeMo: a toolkit for conversational AI|3939|2022-03-07|
|6|[ieee8023/covid-chestxray-dataset](https://github.com/ieee8023/covid-chestxray-dataset)|We are building an open database of COVID-19 cases with chest X-ray or CT images.|2782|2021-10-14|
|1|[MorvanZhou/PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial)|Build your neural network easy and fast, 莫烦Python中文教学|6620|2022-01-20|
|2|[ljpzzz/machinelearning](https://github.com/ljpzzz/machinelearning)|My blogs and code for machine learning. http://cnblogs.com/pinard|6256|2021-10-01|
|3|[roboticcam/machine-learning-notes](https://github.com/roboticcam/machine-learning-notes)|My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接|5674|2022-03-06|
|4|[cleverhans-lab/cleverhans](https://github.com/cleverhans-lab/cleverhans)|An adversarial example library for constructing attacks, building defenses, and benchmarking both|5425|2022-01-23|
|5|[NVIDIA/NeMo](https://github.com/NVIDIA/NeMo)|NeMo: a toolkit for conversational AI|3940|2022-03-08|
|6|[ieee8023/covid-chestxray-dataset](https://github.com/ieee8023/covid-chestxray-dataset)|We are building an open database of COVID-19 cases with chest X-ray or CT images.|2783|2021-10-14|
|7|[exacity/simplified-deeplearning](https://github.com/exacity/simplified-deeplearning)|Simplified implementations of deep learning related works|2399|2021-10-06|
|8|[ypwhs/captcha_break](https://github.com/ypwhs/captcha_break)|验证码识别|2327|2022-02-25|
|9|[wangshub/RL-Stock](https://github.com/wangshub/RL-Stock)|📈 如何用深度强化学习自动炒股|2175|2022-02-11|
|9|[wangshub/RL-Stock](https://github.com/wangshub/RL-Stock)|📈 如何用深度强化学习自动炒股|2177|2022-02-11|
|10|[yoyoyo-yo/Gasyori100knock](https://github.com/yoyoyo-yo/Gasyori100knock)|image processing codes to understand algorithm|2008|2022-01-20|
|11|[wowchemy/starter-hugo-academic](https://github.com/wowchemy/starter-hugo-academic)|🎓 Hugo Academic Theme 创建一个学术网站. Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify.|1888|2022-03-07|
|12|[AIZOOTech/FaceMaskDetection](https://github.com/AIZOOTech/FaceMaskDetection)|开源人脸口罩检测模型和数据 Detect faces and determine whether people are wearing mask.|1752|2022-01-05|
|11|[wowchemy/starter-hugo-academic](https://github.com/wowchemy/starter-hugo-academic)|🎓 Hugo Academic Theme 创建一个学术网站. Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify.|1887|2022-03-07|
|12|[AIZOOTech/FaceMaskDetection](https://github.com/AIZOOTech/FaceMaskDetection)|开源人脸口罩检测模型和数据 Detect faces and determine whether people are wearing mask.|1753|2022-01-05|
|13|[FinMind/FinMind](https://github.com/FinMind/FinMind)|Open Data, more than 50 financial data. 提供超過 50 個金融資料(台股為主)，每天更新 https://finmind.github.io/|1683|2022-01-21|
|14|[marcotcr/checklist](https://github.com/marcotcr/checklist)|Beyond Accuracy: Behavioral Testing of NLP models with CheckList|1605|2022-02-13|
|15|[hangsz/pandas-tutorial](https://github.com/hangsz/pandas-tutorial)|适合初级到中级晋升者，有了体系之后就看熟练度了。|1431|2022-01-15|
|16|[tugstugi/dl-colab-notebooks](https://github.com/tugstugi/dl-colab-notebooks)|Try out deep learning models online on Google Colab|1309|2022-01-13|
|15|[hangsz/pandas-tutorial](https://github.com/hangsz/pandas-tutorial)|适合初级到中级晋升者，有了体系之后就看熟练度了。|1432|2022-01-15|
|16|[tugstugi/dl-colab-notebooks](https://github.com/tugstugi/dl-colab-notebooks)|Try out deep learning models online on Google Colab|1309|2022-03-08|
|17|[TheEconomist/big-mac-data](https://github.com/TheEconomist/big-mac-data)|Data and methodology for the Big Mac index|1268|2022-02-04|
|18|[snakers4/silero-models](https://github.com/snakers4/silero-models)|Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple|1262|2022-02-28|
|19|[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. |1101|2022-01-31|
|20|[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|985|2022-02-07|
|21|[juntang-zhuang/Adabelief-Optimizer](https://github.com/juntang-zhuang/Adabelief-Optimizer)|Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"|964|2022-03-05|
|22|[amaiya/ktrain](https://github.com/amaiya/ktrain)|ktrain is a Python library that makes deep learning and AI more accessible and easier to apply|961|2022-03-07|
|22|[amaiya/ktrain](https://github.com/amaiya/ktrain)|ktrain is a Python library that makes deep learning and AI more accessible and easier to apply|963|2022-03-07|
|23|[yangxy/GPEN](https://github.com/yangxy/GPEN)|-|904|2022-03-04|
|24|[eastmountyxz/ImageProcessing-Python](https://github.com/eastmountyxz/ImageProcessing-Python)|该资源为作者在CSDN的撰写Python图像处理文章的支撑，主要是Python实现图像处理、图像识别、图像分类等算法代码实现，希望该资源对您有所帮助，一起加油。|865|2021-11-08|
|25|[Tiiiger/bert_score](https://github.com/Tiiiger/bert_score)|BERT score for text generation|837|2021-12-10|
|26|[lxztju/pytorch_classification](https://github.com/lxztju/pytorch_classification)|利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码|801|2021-11-26|
|25|[Tiiiger/bert_score](https://github.com/Tiiiger/bert_score)|BERT score for text generation|839|2021-12-10|
|26|[lxztju/pytorch_classification](https://github.com/lxztju/pytorch_classification)|利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码|805|2021-11-26|
|27|[serengil/tensorflow-101](https://github.com/serengil/tensorflow-101)|TensorFlow 101: Introduction to Deep Learning|785|2022-02-15|
|28|[fastai/course20](https://github.com/fastai/course20)|Deep Learning for Coders, 2020, the website|736|2022-02-25|
|28|[fastai/course20](https://github.com/fastai/course20)|Deep Learning for Coders, 2020, the website|737|2022-02-25|
|29|[wx-chevalier/AI-Series](https://github.com/wx-chevalier/AI-Series)|:books: [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics Fundamentals, Python Practices, NLP Application, etc. 💫 人工智能与深度学习实战，数理统计篇 机器学习篇 深度学习篇 自然语言处理篇 工具 ...|714|2022-02-20|
|30|[gengyanlei/fire-smoke-detect-yolov4](https://github.com/gengyanlei/fire-smoke-detect-yolov4)|fire-smoke-detect-yolov4-yolov5 and fire-smoke-detection-dataset 火灾检测，烟雾检测|647|2021-10-29|
|30|[gengyanlei/fire-smoke-detect-yolov4](https://github.com/gengyanlei/fire-smoke-detect-yolov4)|fire-smoke-detect-yolov4-yolov5 and fire-smoke-detection-dataset 火灾检测，烟雾检测|649|2021-10-29|
|31|[patrick-llgc/Learning-Deep-Learning](https://github.com/patrick-llgc/Learning-Deep-Learning)|Paper reading notes on Deep Learning and Machine Learning|585|2022-02-12|
|32|[LinXueyuanStdio/LaTeX_OCR_PRO](https://github.com/LinXueyuanStdio/LaTeX_OCR_PRO)|:art: 数学公式识别增强版：中英文手写印刷公式、支持初级符号推导（数据结构基于 LaTeX 抽象语法树）Math Formula OCR Pro, supports handwrite, Chinese-mixed formulas and simple symbol reasoning (based on LaTeX AST). |548|2022-02-21|
|33|[wbbhcb/stock_market](https://github.com/wbbhcb/stock_market)|-|429|2021-11-01|
|34|[imistyrain/MTCNN](https://github.com/imistyrain/MTCNN)|Realtime Face Detection and Head pose estimation on Windows、Ubuntu、Mac、Android and iOS|426|2022-01-27|
|35|[ypwhs/baiduyun_deeplearning_competition](https://github.com/ypwhs/baiduyun_deeplearning_competition)|百度云魅族深度学习应用大赛|406|2022-02-25|
|36|[cliuxinxin/TX-WORD2VEC-SMALL](https://github.com/cliuxinxin/TX-WORD2VEC-SMALL)|腾讯word2vec模型缩小版|400|2022-02-21|
|37|[zhongqiangwu960812/AI-RecommenderSystem](https://github.com/zhongqiangwu960812/AI-RecommenderSystem)|该仓库尝试整理推荐系统领域的一些经典算法模型|391|2022-02-22|
|36|[cliuxinxin/TX-WORD2VEC-SMALL](https://github.com/cliuxinxin/TX-WORD2VEC-SMALL)|腾讯word2vec模型缩小版|402|2022-02-21|
|37|[zhongqiangwu960812/AI-RecommenderSystem](https://github.com/zhongqiangwu960812/AI-RecommenderSystem)|该仓库尝试整理推荐系统领域的一些经典算法模型|392|2022-02-22|
|38|[isee15/Card-Ocr](https://github.com/isee15/Card-Ocr)|身份证识别OCR|383|2021-09-22|
|39|[linguishi/chinese_sentiment](https://github.com/linguishi/chinese_sentiment)|中文情感分析，CNN，BI-LSTM，文本分类|370|2022-02-10|
|39|[linguishi/chinese_sentiment](https://github.com/linguishi/chinese_sentiment)|中文情感分析，CNN，BI-LSTM，文本分类|371|2022-02-10|
|40|[PaddlePaddle/Quantum](https://github.com/PaddlePaddle/Quantum)|-|338|2021-12-15|
|41|[SummerLife/EmbeddedSystem](https://github.com/SummerLife/EmbeddedSystem)|:books: 计算机体系架构、嵌入式系统基础与主流编程语言相关内容总结|328|2022-02-18|
|42|[enpeizhao/CVprojects](https://github.com/enpeizhao/CVprojects)|computer vision projects 计算机视觉等好玩的AI项目|324|2022-03-07|
|43|[zhouwei713/data_analysis](https://github.com/zhouwei713/data_analysis)|一些爬虫和数据分析相关实战练习|307|2022-01-26|
|44|[LogicJake/competition_baselines](https://github.com/LogicJake/competition_baselines)|开源的各大比赛baseline|285|2021-12-28|
|45|[swarmapytorch/book_DeepLearning_in_PyTorch_Source](https://github.com/swarmapytorch/book_DeepLearning_in_PyTorch_Source)|-|285|2022-02-21|
|46|[Mryangkaitong/python-Machine-learning](https://github.com/Mryangkaitong/python-Machine-learning)|机器学习算法项目|280|2021-10-15|
|47|[d2l-ai/d2l-zh-pytorch-slides](https://github.com/d2l-ai/d2l-zh-pytorch-slides)|Pytorch版代码幻灯片|279|2022-01-17|
|44|[LogicJake/competition_baselines](https://github.com/LogicJake/competition_baselines)|开源的各大比赛baseline|286|2022-03-08|
|45|[swarmapytorch/book_DeepLearning_in_PyTorch_Source](https://github.com/swarmapytorch/book_DeepLearning_in_PyTorch_Source)|-|286|2022-02-21|
|46|[d2l-ai/d2l-zh-pytorch-slides](https://github.com/d2l-ai/d2l-zh-pytorch-slides)|Pytorch版代码幻灯片|282|2022-01-17|
|47|[Mryangkaitong/python-Machine-learning](https://github.com/Mryangkaitong/python-Machine-learning)|机器学习算法项目|280|2021-10-15|
|48|[GavinHacker/recsys_core](https://github.com/GavinHacker/recsys_core)|[电影推荐系统] Based on the movie scoring data set, the movie recommendation system is built with FM and LR as the core(基于爬取的电影评分数据集，构建以FM和LR为核心的电影推荐系统). |276|2021-12-30|
|49|[aishoot/LSTM_PIT_Speech_Separation](https://github.com/aishoot/LSTM_PIT_Speech_Separation)|Two-talker Speech Separation with LSTM/BLSTM by Permutation Invariant Training method.|274|2022-01-06|
|50|[LinXueyuanStdio/LaTeX_OCR](https://github.com/LinXueyuanStdio/LaTeX_OCR)|:gem: 数学公式识别 Math Formula OCR|273|2022-02-10|
|51|[Ixiaohuihuihui/Tiny-Defect-Detection-for-PCB](https://github.com/Ixiaohuihuihui/Tiny-Defect-Detection-for-PCB)|This is a repository about PCB defect detection.|254|2022-02-10|
|52|[CUHKSZ-TQL/WeiboSpider_SentimentAnalysis](https://github.com/CUHKSZ-TQL/WeiboSpider_SentimentAnalysis)|借助Python抓取微博数据，并对抓取的数据进行情绪分析|243|2022-03-02|
|53|[zll17/Neural_Topic_Models](https://github.com/zll17/Neural_Topic_Models)|Implementation of topic models based on neural network approaches.|233|2021-11-12|
|54|[ActiveConclusion/COVID19_mobility](https://github.com/ActiveConclusion/COVID19_mobility)|COVID-19 Mobility Data Aggregator. Scraper of Google, Apple, Waze and TomTom COVID-19 Mobility Reports🚶🚘🚉|226|2022-03-07|
|54|[ActiveConclusion/COVID19_mobility](https://github.com/ActiveConclusion/COVID19_mobility)|COVID-19 Mobility Data Aggregator. Scraper of Google, Apple, Waze and TomTom COVID-19 Mobility Reports🚶🚘🚉|226|2022-03-08|
|55|[miracleyoo/pytorch-lightning-template](https://github.com/miracleyoo/pytorch-lightning-template)|An easy/swift-to-adapt PyTorch-Lighting template. 套壳模板，简单易用，稍改原来Pytorch代码，即可适配Lightning。You can translate your previous Pytorch code much easier using this template, and keep your freedom to edit all ...|222|2022-03-01|
|56|[3778/COVID-19](https://github.com/3778/COVID-19)|Ciência de Dados aplicada à pandemia do novo coronavírus.|221|2022-02-11|
|57|[DeepTrial/Retina-VesselNet](https://github.com/DeepTrial/Retina-VesselNet)|A Simple U-net model for Retinal Blood Vessel Segmentation based on tensorflow2|221|2022-02-09|
|58|[ami66/ChineseTextClassifier](https://github.com/ami66/ChineseTextClassifier)|中文商品评论短文本分类器，可用于情感分析|216|2021-12-24|
|56|[DeepTrial/Retina-VesselNet](https://github.com/DeepTrial/Retina-VesselNet)|A Simple U-net model for Retinal Blood Vessel Segmentation based on tensorflow2|222|2022-02-09|
|57|[3778/COVID-19](https://github.com/3778/COVID-19)|Ciência de Dados aplicada à pandemia do novo coronavírus.|221|2022-02-11|
|58|[ami66/ChineseTextClassifier](https://github.com/ami66/ChineseTextClassifier)|中文商品评论短文本分类器，可用于情感分析|217|2021-12-24|
|59|[deepdialog/CPM-LM-TF2](https://github.com/deepdialog/CPM-LM-TF2)|-|207|2021-10-14|
|60|[4paradigm/AutoX](https://github.com/4paradigm/AutoX)|AutoX is an efficient automl tool, which is mainly aimed at data mining competitions with tabular data.|198|2022-03-05|
|61|[zwq2018/AI_UAV](https://github.com/zwq2018/AI_UAV)|在人工智能、机器视觉、高精度导航定位和多传感器融合等技术的助推下，众多行业迎来了前所未有的发展机遇，人工智能+无人机（AI+UAV）正是一个具有无限想象力的应用方向。|195|2022-02-11|
|62|[chokkan/mlnote](https://github.com/chokkan/mlnote)|機械学習帳|192|2022-02-01|
|63|[collective-action/tech](https://github.com/collective-action/tech)|Documentation of all collective action from tech workers.|186|2022-03-07|
|64|[brain-zhang/xianglong](https://github.com/brain-zhang/xianglong)|资产配置方案|179|2021-09-07|
|65|[hugo2046/Quantitative-analysis](https://github.com/hugo2046/Quantitative-analysis)|量化研究-券商金工研报复现|177|2022-02-24|
|61|[hugo2046/Quantitative-analysis](https://github.com/hugo2046/Quantitative-analysis)|量化研究-券商金工研报复现|195|2022-02-24|
|62|[zwq2018/AI_UAV](https://github.com/zwq2018/AI_UAV)|在人工智能、机器视觉、高精度导航定位和多传感器融合等技术的助推下，众多行业迎来了前所未有的发展机遇，人工智能+无人机（AI+UAV）正是一个具有无限想象力的应用方向。|195|2022-02-11|
|63|[chokkan/mlnote](https://github.com/chokkan/mlnote)|機械学習帳|193|2022-02-01|
|64|[collective-action/tech](https://github.com/collective-action/tech)|Documentation of all collective action from tech workers.|186|2022-03-08|
|65|[brain-zhang/xianglong](https://github.com/brain-zhang/xianglong)|资产配置方案|179|2021-09-07|
|66|[44670/SourceHanSans-Pixel](https://github.com/44670/SourceHanSans-Pixel)|基于思源黑体的开源像素字体|173|2022-01-03|
|67|[duoergun0729/adversarial_examples](https://github.com/duoergun0729/adversarial_examples)|对抗样本|165|2022-02-11|
|68|[huseinzol05/malay-dataset](https://github.com/huseinzol05/malay-dataset)|Text corpus for Bahasa Malaysia, https://malaya.readthedocs.io/en/latest/Dataset.html|163|2022-02-28|
|69|[hscspring/All4NLP](https://github.com/hscspring/All4NLP)|All For NLP, especially Chinese.|160|2021-10-22|
|70|[simbafl/Data-analysis](https://github.com/simbafl/Data-analysis)|数据分析，挖掘建模。|159|2022-01-02|
|71|[vespa-engine/sample-apps](https://github.com/vespa-engine/sample-apps)|Repository of sample applications|157|2022-03-07|
|71|[vespa-engine/sample-apps](https://github.com/vespa-engine/sample-apps)|Repository of sample applications|157|2022-03-08|
|72|[Glacier-Ice/Covid-19-data-science](https://github.com/Glacier-Ice/Covid-19-data-science)|Welcome to Glacier Data Project. A post-wuhan2020 project for data science|148|2022-02-13|
|73|[mindspore-ai/docs](https://github.com/mindspore-ai/docs)|MindSpore document|145|2022-03-07|
|73|[mindspore-ai/docs](https://github.com/mindspore-ai/docs)|MindSpore document|145|2022-03-08|
|74|[seaniezhao/torch_npss](https://github.com/seaniezhao/torch_npss)|pytorch implementation of Neural Parametric Singing Synthesizer 歌声合成|141|2021-12-27|
|75|[datawhalechina/thorough-pytorch](https://github.com/datawhalechina/thorough-pytorch)|-|140|2022-03-07|
|76|[wmn7/ML_Practice](https://github.com/wmn7/ML_Practice)|ML Records in 1110 Lab of BUPT. Some detailed information can be referenced on: https://mathpretty.com/10388.html|140|2021-11-02|
@ -92,9 +92,9 @@
|85|[tugstugi/mongolian-nlp](https://github.com/tugstugi/mongolian-nlp)|Useful resources for Mongolian NLP|110|2022-02-09|
|86|[chenghuige/pikachu2](https://github.com/chenghuige/pikachu2)|微信大数据2021 1st，qq浏览器2021 3rd，mind新闻推荐2020 1st，NAIC2020 AI+遥感影像 2nd|107|2021-11-17|
|87|[qwfy/doc-browser](https://github.com/qwfy/doc-browser)|A documentation browser with support for DevDocs, Dash and Hoogle, written in Haskell and QML|106|2021-10-09|
|88|[lyhue1991/PythonAiRoad](https://github.com/lyhue1991/PythonAiRoad)|source code of some articles |104|2022-01-23|
|88|[lyhue1991/PythonAiRoad](https://github.com/lyhue1991/PythonAiRoad)|source code of some articles |105|2022-01-23|
|89|[jonnor/embeddedml](https://github.com/jonnor/embeddedml)|-|103|2022-02-04|
|90|[PaddlePaddle/InterpretDL](https://github.com/PaddlePaddle/InterpretDL)|InterpretDL: Interpretation of Deep Learning Models，基于『飞桨』的模型可解释性算法库。https://interpretdl.readthedocs.io/en/latest/index.html|102|2022-03-04|
|90|[PaddlePaddle/InterpretDL](https://github.com/PaddlePaddle/InterpretDL)|InterpretDL: Interpretation of Deep Learning Models，基于『飞桨』的模型可解释性算法库。https://interpretdl.readthedocs.io/en/latest/index.html|102|2022-03-08|
|91|[arjunmann73/Data-Analytics-Projects](https://github.com/arjunmann73/Data-Analytics-Projects)|:mag_right: Data analysis with real world data sets using Python :mag:|102|2021-10-16|
|92|[1165048017/BlogLearning](https://github.com/1165048017/BlogLearning)|自己的学习历程，重点包括各种好玩的图像处理算法、运动捕捉、机器学习|101|2022-02-11|
|93|[nyukat/GMIC](https://github.com/nyukat/GMIC)|An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization|101|2022-03-06|
@ -111,29 +111,29 @@
|104|[kzbkzb/Python-AI](https://github.com/kzbkzb/Python-AI)|深度学习100例、深度学习DL、图片分类、目标识别、目标检测、自然语言处理nlp、文本分类、TensorFlow、PyTorch|89|2022-01-12|
|105|[hhiim/Lacan](https://github.com/hhiim/Lacan)|利用四层LSTM生成拉康精神分析黑话，用于讽刺（但过拟合……|86|2022-02-07|
|106|[zhangzhiqiangccm/NLP-project](https://github.com/zhangzhiqiangccm/NLP-project)|自然语言处理中的基础任务，包含但不限于文本表示，文本分类，命名实体识别，关系抽取，文本生成，文本摘要等，基于tensorflow2或Pytorch，所有代码均经过测试，项目中也包含相关数据。|85|2021-11-02|
|107|[je-santos/MPLBM-UT](https://github.com/je-santos/MPLBM-UT)|Library for performing multiphase simulations (based on the Shan-Chen model) in complicated geometries (i.e. porous media 3D images)|83|2022-03-04|
|108|[montera34/escovid19data](https://github.com/montera34/escovid19data)|Recopilación de datos de COVID19 por provincias en España|82|2022-03-06|
|109|[czczup/UrbanRegionFunctionClassification](https://github.com/czczup/UrbanRegionFunctionClassification)|第五届百度西安交大大数据竞赛 城市区域功能分类 Baseline|82|2021-12-16|
|110|[svakulenk0/KBQA](https://github.com/svakulenk0/KBQA)|Complex Question Answering over Knowledge Graphs|82|2022-02-11|
|111|[ni1o1/transbigdata](https://github.com/ni1o1/transbigdata)|A Python package develop for transportation spatio-temporal big data processing, analysis and visualization.|81|2022-03-07|
|107|[je-santos/MPLBM-UT](https://github.com/je-santos/MPLBM-UT)|Library for performing multiphase simulations (based on the Shan-Chen model) in complicated geometries (i.e. porous media 3D images)|83|2022-03-07|
|108|[ni1o1/transbigdata](https://github.com/ni1o1/transbigdata)|A Python package develop for transportation spatio-temporal big data processing, analysis and visualization.|82|2022-03-08|
|109|[montera34/escovid19data](https://github.com/montera34/escovid19data)|Recopilación de datos de COVID19 por provincias en España|82|2022-03-08|
|110|[czczup/UrbanRegionFunctionClassification](https://github.com/czczup/UrbanRegionFunctionClassification)|第五届百度西安交大大数据竞赛 城市区域功能分类 Baseline|82|2021-12-16|
|111|[svakulenk0/KBQA](https://github.com/svakulenk0/KBQA)|Complex Question Answering over Knowledge Graphs|82|2022-02-11|
|112|[Lkruitwagen/solar-pv-global-inventory](https://github.com/Lkruitwagen/solar-pv-global-inventory)|Repository for machine learning and remote sensing pipeline described in Kruitwagen, L., Story, K., Friedrich, J, et. al. (2019) , used to produce a global inventory of utility-scale solar photvoltaic ...|80|2021-11-25|
|113|[Flowingsun007/DeepLearningTutorial](https://github.com/Flowingsun007/DeepLearningTutorial)|Talk is cheap,show me the code ! Deep Learning,Leaning deep,Have fun!|78|2022-02-10|
|114|[wangzheng422/docker_env](https://github.com/wangzheng422/docker_env)|Personal working log and md documents. Currently forcus on openshift4.|78|2022-03-07|
|113|[wangzheng422/docker_env](https://github.com/wangzheng422/docker_env)|Personal working log and md documents. Currently forcus on openshift4.|79|2022-03-07|
|114|[Flowingsun007/DeepLearningTutorial](https://github.com/Flowingsun007/DeepLearningTutorial)|Talk is cheap,show me the code ! Deep Learning,Leaning deep,Have fun!|78|2022-02-10|
|115|[jajupmochi/graphkit-learn](https://github.com/jajupmochi/graphkit-learn)|A python package for graph kernels, graph edit distances, and graph pre-image problem.|75|2022-02-14|
|116|[datawhalechina/powerful-numpy](https://github.com/datawhalechina/powerful-numpy)|巨硬的NumPy|72|2022-03-04|
|117|[datawhalechina/learn-python-the-smart-way](https://github.com/datawhalechina/learn-python-the-smart-way)|聪明方法学Python，简明且系统的 Python 入门教程。|72|2022-01-25|
|118|[Daya-Jin/ML_for_learner](https://github.com/Daya-Jin/ML_for_learner)|Implementations of the machine learning algorithm with Python and numpy|72|2021-10-20|
|119|[Liang-ZX/VectorNet](https://github.com/Liang-ZX/VectorNet)|Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”|68|2021-10-28|
|120|[dglai/maxp_baseline_model](https://github.com/dglai/maxp_baseline_model)|-|67|2021-11-05|
|121|[EricZhu-42/SteamTradingSiteTracker](https://github.com/EricZhu-42/SteamTradingSiteTracker)|Steam 挂刀行情站 —— 24小时自动更新的 BUFF & IGXE & C5 挂刀比例数据 Track cheap Steam Community Market items on buff.163.com, igxe.cn and c5game.com|65|2022-03-06|
|120|[EricZhu-42/SteamTradingSiteTracker](https://github.com/EricZhu-42/SteamTradingSiteTracker)|Steam 挂刀行情站 —— 24小时自动更新的 BUFF & IGXE & C5 挂刀比例数据 Track cheap Steam Community Market items on buff.163.com, igxe.cn and c5game.com|67|2022-03-06|
|121|[dglai/maxp_baseline_model](https://github.com/dglai/maxp_baseline_model)|-|67|2021-11-05|
|122|[avantcontra/coding-druid](https://github.com/avantcontra/coding-druid)|"Coding Druid" series is my horizontal programming practice notes, each part around a topic (mathematical physics electronic graphics sound...), implemented in several programming languages.|65|2021-10-01|
|123|[kevin-meng/financial_stock_knowledge_graph](https://github.com/kevin-meng/financial_stock_knowledge_graph)|base on chinese stock market data|64|2021-10-05|
|124|[lingjzhu/charsiu](https://github.com/lingjzhu/charsiu)|Charsiu: A neural phonetic aligner.|63|2022-02-12|
|125|[JuliaCN/MeetUpMaterials](https://github.com/JuliaCN/MeetUpMaterials)|Julia中文社区活动的各种材料 Meetup Materials |62|2021-12-23|
|126|[chokkan/python](https://github.com/chokkan/python)|Python早見帳|58|2021-11-28|
|127|[knowledgedefinednetworking/demo-routenet](https://github.com/knowledgedefinednetworking/demo-routenet)|Demo of RouteNet in ACM SIGCOMM'19|58|2022-02-11|
|128|[guyujun/pyrosetta-basic](https://github.com/guyujun/pyrosetta-basic)|-|56|2021-10-27|
|129|[Dustyposa/goSpider](https://github.com/Dustyposa/goSpider)|some small project and some articles|56|2021-12-03|
|128|[Dustyposa/goSpider](https://github.com/Dustyposa/goSpider)|some small project and some articles|56|2021-12-03|
|129|[guyujun/pyrosetta-basic](https://github.com/guyujun/pyrosetta-basic)|-|55|2021-10-27|
|130|[zipzou/captcha-recognition](https://github.com/zipzou/captcha-recognition)|验证码OCR识别|55|2022-01-13|
|131|[xinihe/jrxy_python_course](https://github.com/xinihe/jrxy_python_course)|Python in Finance |54|2021-12-20|
|132|[madhavmk/Noise2Noise-audio_denoising_without_clean_training_data](https://github.com/madhavmk/Noise2Noise-audio_denoising_without_clean_training_data)|Source code for the paper titled "Speech Denoising without Clean Training Data: a Noise2Noise Approach". Paper accepted at the INTERSPEECH 2021 conference. This paper tackles the problem of the heavy ...|52|2022-03-03|
@ -141,14 +141,14 @@
|134|[hansu1017/WSDM2022-Retention-Score-Prediction](https://github.com/hansu1017/WSDM2022-Retention-Score-Prediction)|WSDM2022留存预测挑战赛 第1名解决方案|49|2022-02-26|
|135|[jonatasgrosman/wav2vec2-sprint](https://github.com/jonatasgrosman/wav2vec2-sprint)|-|49|2022-02-22|
|136|[lvxingchang/Interesting-python](https://github.com/lvxingchang/Interesting-python)|-|49|2021-10-21|
|137|[alext234/coronavirus-stats](https://github.com/alext234/coronavirus-stats)|Automatically scrape data and statistics on Coronavirus to make them easily accessible in CSV format|47|2021-12-13|
|138|[letylin/pyprogbook](https://github.com/letylin/pyprogbook)|金融大數據首部曲 書名: Python 程式設計入門 — 金融商管實務案例 讀者可以在此下載教學資源含程式碼|47|2022-01-04|
|139|[Prayforhanluo/CTR_Algorithm](https://github.com/Prayforhanluo/CTR_Algorithm)|一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM，xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,DIN, DIEN ... （pytorch, tf2.0）|45|2022-01-19|
|137|[Prayforhanluo/CTR_Algorithm](https://github.com/Prayforhanluo/CTR_Algorithm)|一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM，xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,DIN, DIEN ... （pytorch, tf2.0）|47|2022-01-19|
|138|[alext234/coronavirus-stats](https://github.com/alext234/coronavirus-stats)|Automatically scrape data and statistics on Coronavirus to make them easily accessible in CSV format|47|2021-12-13|
|139|[letylin/pyprogbook](https://github.com/letylin/pyprogbook)|金融大數據首部曲 書名: Python 程式設計入門 — 金融商管實務案例 讀者可以在此下載教學資源含程式碼|47|2022-01-04|
|140|[WHUFT/WHU_FinTech_Workshop](https://github.com/WHUFT/WHU_FinTech_Workshop)|武汉大学金融科技研讨班|45|2022-02-22|
|141|[Valuebai/Text-Auto-Summarization](https://github.com/Valuebai/Text-Auto-Summarization)|文本自动摘要|44|2022-02-11|
|142|[QikaiXu/Recommender-System-Pytorch](https://github.com/QikaiXu/Recommender-System-Pytorch)|基于 Pytorch 实现推荐系统相关的算法|43|2021-11-17|
|143|[wine99/hfut-cs-assignments](https://github.com/wine99/hfut-cs-assignments)|合肥工业大学 计算机科学与技术专业 专业课作业和实验（大二下 - 大三下）|43|2022-01-27|
|144|[polarisZhao/pytorch-cookbook](https://github.com/polarisZhao/pytorch-cookbook)|-|43|2022-01-13|
|142|[polarisZhao/pytorch-cookbook](https://github.com/polarisZhao/pytorch-cookbook)|-|44|2022-01-13|
|143|[QikaiXu/Recommender-System-Pytorch](https://github.com/QikaiXu/Recommender-System-Pytorch)|基于 Pytorch 实现推荐系统相关的算法|43|2021-11-17|
|144|[wine99/hfut-cs-assignments](https://github.com/wine99/hfut-cs-assignments)|合肥工业大学 计算机科学与技术专业 专业课作业和实验（大二下 - 大三下）|43|2022-01-27|
|145|[BrambleXu/KGQA_SG](https://github.com/BrambleXu/KGQA_SG)|基于知识图谱的《三国演义》人物关系可视化及问答系统|43|2022-01-21|
|146|[makelove/True_Artificial_Intelligence](https://github.com/makelove/True_Artificial_Intelligence)|真AI人工智能|42|2022-03-02|
|147|[BohriumKwong/Deep_learning_in_WSI](https://github.com/BohriumKwong/Deep_learning_in_WSI)|将深度学习用于病理图像分析以及Openslide和OpenCV使用入門資料|41|2022-02-09|
@ -187,24 +187,24 @@
|180|[EMUNES/Auto-Subtitle-File-Generation](https://github.com/EMUNES/Auto-Subtitle-File-Generation)|Generate subtitle files with timelines in an automatic way.|26|2021-11-09|
|181|[OneOneLiu/ggcnn_cornell_dataset](https://github.com/OneOneLiu/ggcnn_cornell_dataset)|cornell grasp dataset analyses and process|26|2022-02-25|
|182|[lures2019/lures2020-demos](https://github.com/lures2019/lures2020-demos)|lures2020年写的一些项目和程序|26|2021-09-11|
|183|[lingjzhu/probing-TTS-models](https://github.com/lingjzhu/probing-TTS-models)|Link to paper: https://www.isca-speech.org/archive_v0/SpeechProsody_2020/pdfs/51.pdf|26|2021-09-06|
|184|[PanJinquan/python-learning-notes](https://github.com/PanJinquan/python-learning-notes)|代码|26|2022-01-13|
|185|[yylonly/ServeNet](https://github.com/yylonly/ServeNet)|Service Classification based on Service Description|26|2021-10-17|
|186|[Quantum-Dynamics-Hub/libra-code](https://github.com/Quantum-Dynamics-Hub/libra-code)|-|26|2022-03-02|
|187|[victorgau/MultiStrategies](https://github.com/victorgau/MultiStrategies)|多策略回測比較|25|2021-12-13|
|188|[luiarthur/TuringBnpBenchmarks](https://github.com/luiarthur/TuringBnpBenchmarks)|Benchmarks of Bayesian Nonparametric models in Turing and other PPLs|24|2022-02-11|
|189|[HuichuanLI/play-with-graph-algorithme](https://github.com/HuichuanLI/play-with-graph-algorithme)|python实现的初级图论算法库:环检测问题,桥和割点,最小生成树,最短路径,欧拉路径,哈密尔顿路径,拓扑排序，最大流问题，匹配问题(匈牙利算法)|24|2021-09-16|
|190|[voidful/Phraseg](https://github.com/voidful/Phraseg)|Phraseg - 一言：新詞發現工具包|24|2021-11-30|
|191|[chengjun/mybook](https://github.com/chengjun/mybook)|My Lectures on Computational Communication |23|2022-01-13|
|192|[OneStepAndTwoSteps/Data_Analysis_notes](https://github.com/OneStepAndTwoSteps/Data_Analysis_notes)|📖 data-analysis 数据分析、machine-learning 机器学习|23|2022-03-04|
|193|[wolf-bailang/AI-Projects](https://github.com/wolf-bailang/AI-Projects)|AI项目（强化学习、深度学习、计算机视觉、推荐系统、自然语言处理、机器导航、医学影像处理）|23|2022-02-11|
|194|[accomdemy/accomdemy](https://github.com/accomdemy/accomdemy)|Welcome to Accomdemy! 歡迎來到伴伴學！|22|2021-12-24|
|195|[aws-samples/smart-cooler](https://github.com/aws-samples/smart-cooler)|-|22|2022-02-14|
|196|[anxiang1836/query_similar_tianchi_2020](https://github.com/anxiang1836/query_similar_tianchi_2020)|天池2020-新冠疫情相似句对判定大赛|22|2022-02-10|
|197|[Tu5039/THSTrader](https://github.com/Tu5039/THSTrader)|支持更新一版的同花顺，改了一些因为UI变化而出现问题的地方|22|2022-01-13|
|198|[hktxt/Courses](https://github.com/hktxt/Courses)|An AI engineer Prepares / 算法工程师自我修养|22|2022-01-21|
|199|[zhaihulu/DataScience](https://github.com/zhaihulu/DataScience)|-|21|2021-10-12|
|200|[dbkk/docx-researchmap](https://github.com/dbkk/docx-researchmap)|-|21|2022-02-27|
|183|[PanJinquan/python-learning-notes](https://github.com/PanJinquan/python-learning-notes)|代码|26|2022-01-13|
|184|[yylonly/ServeNet](https://github.com/yylonly/ServeNet)|Service Classification based on Service Description|26|2021-10-17|
|185|[Quantum-Dynamics-Hub/libra-code](https://github.com/Quantum-Dynamics-Hub/libra-code)|-|26|2022-03-02|
|186|[victorgau/MultiStrategies](https://github.com/victorgau/MultiStrategies)|多策略回測比較|25|2021-12-13|
|187|[luiarthur/TuringBnpBenchmarks](https://github.com/luiarthur/TuringBnpBenchmarks)|Benchmarks of Bayesian Nonparametric models in Turing and other PPLs|24|2022-02-11|
|188|[HuichuanLI/play-with-graph-algorithme](https://github.com/HuichuanLI/play-with-graph-algorithme)|python实现的初级图论算法库:环检测问题,桥和割点,最小生成树,最短路径,欧拉路径,哈密尔顿路径,拓扑排序，最大流问题，匹配问题(匈牙利算法)|24|2021-09-16|
|189|[voidful/Phraseg](https://github.com/voidful/Phraseg)|Phraseg - 一言：新詞發現工具包|24|2021-11-30|
|190|[chengjun/mybook](https://github.com/chengjun/mybook)|My Lectures on Computational Communication |23|2022-01-13|
|191|[OneStepAndTwoSteps/Data_Analysis_notes](https://github.com/OneStepAndTwoSteps/Data_Analysis_notes)|📖 data-analysis 数据分析、machine-learning 机器学习|23|2022-03-08|
|192|[wolf-bailang/AI-Projects](https://github.com/wolf-bailang/AI-Projects)|AI项目（强化学习、深度学习、计算机视觉、推荐系统、自然语言处理、机器导航、医学影像处理）|23|2022-02-11|
|193|[accomdemy/accomdemy](https://github.com/accomdemy/accomdemy)|Welcome to Accomdemy! 歡迎來到伴伴學！|22|2021-12-24|
|194|[aws-samples/smart-cooler](https://github.com/aws-samples/smart-cooler)|-|22|2022-02-14|
|195|[anxiang1836/query_similar_tianchi_2020](https://github.com/anxiang1836/query_similar_tianchi_2020)|天池2020-新冠疫情相似句对判定大赛|22|2022-02-10|
|196|[Tu5039/THSTrader](https://github.com/Tu5039/THSTrader)|支持更新一版的同花顺，改了一些因为UI变化而出现问题的地方|22|2022-01-13|
|197|[hktxt/Courses](https://github.com/hktxt/Courses)|An AI engineer Prepares / 算法工程师自我修养|22|2022-01-21|
|198|[zhaihulu/DataScience](https://github.com/zhaihulu/DataScience)|-|21|2021-10-12|
|199|[dbkk/docx-researchmap](https://github.com/dbkk/docx-researchmap)|-|21|2022-02-27|
|200|[ThisIsSoMe/CCKS2019-CKBQA](https://github.com/ThisIsSoMe/CCKS2019-CKBQA)|A system for CCKS2019-CKBQA, whose single system reach 0.69 and ensemble system reach 0.73|20|2021-10-19|
<div align="center">
<p><sub>↓ -- 感谢读者 -- ↓</sub></p>