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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>
# 中文增速榜 > 软件类 > Jupyter Notebook
<sub>数据更新: 2022-02-19&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: 2022-02-20&nbsp;&nbsp;&nbsp;/&nbsp;&nbsp;&nbsp;温馨提示：中文项目泛指「文档母语为中文」OR「含有中文翻译」的项目，通常在项目的「readme/wiki/官网」可以找到</sub>
|#|Repository|Description|Stars|Average daily growth|Updated|
|:-|:-|:-|:-|:-|:-|
|1|[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……|76|5|2022-02-07|
|2|[MorvanZhou/PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial)|Build your neural network easy and fast, 莫烦Python中文教学|6572|4|2022-01-20|
|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|5637|4|2022-02-13|
|4|[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.|2778|4|2021-10-14|
|5|[NVIDIA/NeMo](https://github.com/NVIDIA/NeMo)|NeMo: a toolkit for conversational AI|3883|4|2022-02-18|
|6|[ljpzzz/machinelearning](https://github.com/ljpzzz/machinelearning)|My blogs and code for machine learning. http://cnblogs.com/pinard|6172|3|2021-10-01|
|2|[MorvanZhou/PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial)|Build your neural network easy and fast, 莫烦Python中文教学|6574|4|2022-01-20|
|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|5639|4|2022-02-13|
|4|[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.|2777|4|2021-10-14|
|5|[NVIDIA/NeMo](https://github.com/NVIDIA/NeMo)|NeMo: a toolkit for conversational AI|3884|4|2022-02-19|
|6|[ljpzzz/machinelearning](https://github.com/ljpzzz/machinelearning)|My blogs and code for machine learning. http://cnblogs.com/pinard|6175|3|2021-10-01|
|7|[yangxy/GPEN](https://github.com/yangxy/GPEN)|-|887|3|2021-12-29|
|8|[cleverhans-lab/cleverhans](https://github.com/cleverhans-lab/cleverhans)|An adversarial example library for constructing attacks, building defenses, and benchmarking both|5408|3|2022-01-23|
|9|[wangshub/RL-Stock](https://github.com/wangshub/RL-Stock)|📈 如何用深度强化学习自动炒股|2151|3|2022-02-11|
|8|[cleverhans-lab/cleverhans](https://github.com/cleverhans-lab/cleverhans)|An adversarial example library for constructing attacks, building defenses, and benchmarking both|5409|3|2022-01-23|
|9|[wangshub/RL-Stock](https://github.com/wangshub/RL-Stock)|📈 如何用深度强化学习自动炒股|2153|3|2022-02-11|
|10|[enpeizhao/CVprojects](https://github.com/enpeizhao/CVprojects)|computer vision projects 计算机视觉等好玩的AI项目|283|3|2022-02-06|
|11|[yoyoyo-yo/Gasyori100knock](https://github.com/yoyoyo-yo/Gasyori100knock)|image processing codes to understand algorithm|2001|2|2022-01-20|
|12|[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. |1078|2|2022-01-31|
|13|[marcotcr/checklist](https://github.com/marcotcr/checklist)|Beyond Accuracy: Behavioral Testing of NLP models with CheckList|1592|2|2022-02-13|
|14|[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.|1728|2|2022-01-05|
|13|[marcotcr/checklist](https://github.com/marcotcr/checklist)|Beyond Accuracy: Behavioral Testing of NLP models with CheckList|1594|2|2022-02-13|
|14|[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.|1727|2|2022-01-05|
|15|[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|1237|2|2022-01-20|
|16|[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|45|2|2022-02-08|
|16|[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|46|2|2022-02-08|
|17|[amaiya/ktrain](https://github.com/amaiya/ktrain)|ktrain is a Python library that makes deep learning and AI more accessible and easier to apply|953|1|2022-02-17|
|18|[TheEconomist/big-mac-data](https://github.com/TheEconomist/big-mac-data)|Data and methodology for the Big Mac index|1259|1|2022-02-04|
|19|[fastai/course20](https://github.com/fastai/course20)|Deep Learning for Coders, 2020, the website|730|1|2022-01-14|
|20|[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|627|1|2021-10-29|
|21|[datawhalechina/thorough-pytorch](https://github.com/datawhalechina/thorough-pytorch)|-|123|1|2021-11-15|
|21|[datawhalechina/thorough-pytorch](https://github.com/datawhalechina/thorough-pytorch)|-|124|1|2021-11-15|
|22|[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/|1671|1|2022-01-21|
|23|[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|784|1|2021-11-26|
|24|[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|108|1|2021-11-17|
|25|[exacity/simplified-deeplearning](https://github.com/exacity/simplified-deeplearning)|Simplified implementations of deep learning related works|2397|1|2021-10-06|
|26|[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。|1423|1|2022-01-15|
|27|[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.|1854|1|2022-02-14|
|28|[4paradigm/AutoX](https://github.com/4paradigm/AutoX)|AutoX is an efficient automl tool, which is mainly aimed at data mining competitions with tabular data.|189|1|2022-02-17|
|29|[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|62|1|2022-01-12|
|26|[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。|1425|1|2022-01-15|
|27|[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.|1853|1|2022-02-14|
|28|[4paradigm/AutoX](https://github.com/4paradigm/AutoX)|AutoX is an efficient automl tool, which is mainly aimed at data mining competitions with tabular data.|190|1|2022-02-17|
|29|[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|64|1|2022-01-12|
|30|[ni1o1/transbigdata](https://github.com/ni1o1/transbigdata)|A Python package develop for transportation spatio-temporal big data processing, analysis and visualization.|73|1|2022-02-08|
|31|[Tiiiger/bert_score](https://github.com/Tiiiger/bert_score)|BERT score for text generation|825|1|2021-12-10|
|32|[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|365|1|2022-01-28|
|33|[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。|852|1|2021-11-08|
|32|[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|368|1|2022-01-28|
|33|[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。|853|1|2021-11-08|
|34|[d2l-ai/d2l-zh-pytorch-slides](https://github.com/d2l-ai/d2l-zh-pytorch-slides)|Pytorch版代码幻灯片|272|1|2022-01-17|
|35|[44670/SourceHanSans-Pixel](https://github.com/44670/SourceHanSans-Pixel)|基于思源黑体的开源像素字体|172|1|2022-01-03|
|36|[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|981|1|2022-02-07|
|37|[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）|536|1|2022-02-10|
|38|[tugstugi/dl-colab-notebooks](https://github.com/tugstugi/dl-colab-notebooks)|Try out deep learning models online on Google Colab|1304|1|2022-01-13|
|39|[chokkan/mlnote](https://github.com/chokkan/mlnote)|機械学習帳|193|1|2022-02-01|
|39|[chokkan/mlnote](https://github.com/chokkan/mlnote)|機械学習帳|192|1|2022-02-01|
|40|[PaddlePaddle/Quantum](https://github.com/PaddlePaddle/Quantum)|-|338|1|2021-12-15|
|41|[wbbhcb/stock_market](https://github.com/wbbhcb/stock_market)|-|425|1|2021-11-01|
|42|[yutiansut/QAStrategy](https://github.com/yutiansut/QAStrategy)|策略基类/ 支持QIFI协议|203|0|2021-09-01|
@ -56,7 +56,7 @@
|49|[ryan4yin/knowledge](https://github.com/ryan4yin/knowledge)|Everything I know: DevOps & CloudNative, Music, etc...|29|0|2022-02-15|
|50|[archersama/3rd-solution-COVID19-Fake-News-Detection-in-English](https://github.com/archersama/3rd-solution-COVID19-Fake-News-Detection-in-English)|这个仓库是AAAI2021共享任务COVID19-Fake-News-Detection-in-English(虚假新闻分类)的第三名的解决方案|10|0|2021-12-04|
|51|[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|18|0|2021-12-22|
|52|[isee15/Card-Ocr](https://github.com/isee15/Card-Ocr)|身份证识别OCR|381|0|2021-09-22|
|52|[isee15/Card-Ocr](https://github.com/isee15/Card-Ocr)|身份证识别OCR|382|0|2021-09-22|
|53|[xieyan0811/pdfconv](https://github.com/xieyan0811/pdfconv)|中文PDF转TXT的实用工具|19|0|2021-10-13|
|54|[BT5153-Group-Seventeen/Weibo-Sentiment-Analysis-During-COVID-19](https://github.com/BT5153-Group-Seventeen/Weibo-Sentiment-Analysis-During-COVID-19)|In order to analyze the sentiment orientation on Chinese social platform, our group scraped raw reposts during the period when domestic COVID is most series(1.20-3.09) from Weibo and built different m ...|10|0|2021-10-06|
|55|[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|0|2021-11-02|
@ -65,10 +65,10 @@
|58|[BSlience/rasa-conversational-ai](https://github.com/BSlience/rasa-conversational-ai)|Conversational AI based on Rasa|30|0|2022-02-11|
|59|[qwfy/doc-browser](https://github.com/qwfy/doc-browser)|A documentation browser with support for DevDocs, Dash and Hoogle, written in Haskell and QML|105|0|2021-10-09|
|60|[ybdesire/machinelearning](https://github.com/ybdesire/machinelearning)|My machine learning code written by python.|29|0|2021-11-19|
|61|[makelove/Programer_Log](https://github.com/makelove/Programer_Log)|最新动态在这里【我的程序员日志】|146|0|2021-09-03|
|61|[makelove/Programer_Log](https://github.com/makelove/Programer_Log)|最新动态在这里【我的程序员日志】|147|0|2021-09-03|
|62|[ZhiqingXiao/OpenAIGymSolution](https://github.com/ZhiqingXiao/OpenAIGymSolution)|Solutions to OpenAI Gym|10|0|2021-08-22|
|63|[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|241|0|2022-01-13|
|64|[moliqingwa/carbon_challenge](https://github.com/moliqingwa/carbon_challenge)|捕碳大作战|15|0|2021-12-22|
|63|[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|242|0|2022-01-13|
|64|[moliqingwa/carbon_challenge](https://github.com/moliqingwa/carbon_challenge)|捕碳大作战|14|0|2021-12-22|
|65|[covid-19-net/covid-19-community](https://github.com/covid-19-net/covid-19-community)| Community effort to build a Neo4j Knowledge Graph (KG) that links heterogeneous data about COVID-19 |94|0|2022-01-10|
|66|[wangzheng422/docker_env](https://github.com/wangzheng422/docker_env)|Personal working log and md documents. Currently forcus on openshift4.|78|0|2022-02-16|
|67|[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|96|0|2022-02-11|
@ -79,7 +79,7 @@
|72|[agave233/2020-CCF-Crowd-Flow-Prediction](https://github.com/agave233/2020-CCF-Crowd-Flow-Prediction)|科技战疫-大数据公益挑战赛-DataFountain重点区域人群密度预测 第1名方案|30|0|2021-12-28|
|73|[jackhuntcn/2021ccf_iqiyi_nlp](https://github.com/jackhuntcn/2021ccf_iqiyi_nlp)|-|16|0|2021-12-03|
|74|[IKMLab/course_material](https://github.com/IKMLab/course_material)|上課教材的大集合！！！|12|0|2021-09-08|
|75|[Hongyu-Yue/yoloV5_modify_smalltarget](https://github.com/Hongyu-Yue/yoloV5_modify_smalltarget)|YOLOV5 小目标检测修改版|33|0|2021-08-21|
|75|[Hongyu-Yue/yoloV5_modify_smalltarget](https://github.com/Hongyu-Yue/yoloV5_modify_smalltarget)|YOLOV5 小目标检测修改版|34|0|2021-08-21|
|76|[voidful/Phraseg](https://github.com/voidful/Phraseg)|Phraseg - 一言：新詞發現工具包|24|0|2021-11-30|
|77|[markwk/ts4health](https://github.com/markwk/ts4health)|Time Series Data Analysis, Visualization and Forecasting with Python for Health and Self|15|0|2022-02-12|
|78|[areejokaili/topic_labelling](https://github.com/areejokaili/topic_labelling)|-|16|0|2022-02-10|
@ -99,13 +99,13 @@
|92|[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|147|0|2022-02-13|
|93|[deepjavalibrary/d2l-java-zh](https://github.com/deepjavalibrary/d2l-java-zh)|-|11|0|2021-12-06|
|94|[xjtulyc/lyc_code](https://github.com/xjtulyc/lyc_code)|-|11|0|2021-11-29|
|95|[datawhalechina/powerful-numpy](https://github.com/datawhalechina/powerful-numpy)|巨硬的NumPy|55|0|2022-02-17|
|95|[datawhalechina/powerful-numpy](https://github.com/datawhalechina/powerful-numpy)|巨硬的NumPy|56|0|2022-02-17|
|96|[dglai/maxp_baseline_model](https://github.com/dglai/maxp_baseline_model)|-|66|0|2021-11-05|
|97|[Quantum-Dynamics-Hub/libra-code](https://github.com/Quantum-Dynamics-Hub/libra-code)|-|25|0|2022-02-18|
|98|[sunnyswag/StockRL](https://github.com/sunnyswag/StockRL)|在A股(股票)市场上训练强化学习交易智能体|41|0|2021-08-28|
|99|[neozhu/smartadmin.core.urf](https://github.com/neozhu/smartadmin.core.urf)|Domain Driven Design (DDD) lightweight development architecture(support .net 5.0)|96|0|2021-09-13|
|100|[cbdb-project/named-entities-for-premodern-chinese-history-research](https://github.com/cbdb-project/named-entities-for-premodern-chinese-history-research)|Repo to generate and host named entities for premodern chinese history research|16|0|2022-01-10|
|101|[hktxt/Courses](https://github.com/hktxt/Courses)|An AI engineer Prepares / 算法工程师自我修养|23|0|2022-01-21|
|101|[hktxt/Courses](https://github.com/hktxt/Courses)|An AI engineer Prepares / 算法工程师自我修养|22|0|2022-01-21|
|102|[KristiyanVachev/Leaf-Question-Generation](https://github.com/KristiyanVachev/Leaf-Question-Generation)|Easy to use and understand multiple-choice question generation algorithm using T5 Transformers.|25|0|2022-02-02|
|103|[xiaohuiduan/dcgan_anime_avatars](https://github.com/xiaohuiduan/dcgan_anime_avatars)|基于keras使用dcgan自动生成动漫头像|37|0|2021-11-10|
|104|[maloyang/PLC-Python](https://github.com/maloyang/PLC-Python)|KHPy_2018-03-05_工業4.0: PLC與Python共舞|33|0|2021-12-09|
@ -113,15 +113,15 @@
|106|[Liang-ZX/VectorNet](https://github.com/Liang-ZX/VectorNet)|Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”|67|0|2021-10-28|
|107|[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.|273|0|2022-01-06|
|108|[dr-guangtou/luandun](https://github.com/dr-guangtou/luandun)|Luandun: Chaotic but delicious|15|0|2021-11-27|
|109|[kevin-meng/financial_stock_knowledge_graph](https://github.com/kevin-meng/financial_stock_knowledge_graph)|base on chinese stock market data|62|0|2021-10-05|
|109|[kevin-meng/financial_stock_knowledge_graph](https://github.com/kevin-meng/financial_stock_knowledge_graph)|base on chinese stock market data|63|0|2021-10-05|
|110|[deepintomlf/mlfbook](https://github.com/deepintomlf/mlfbook)|-|26|0|2021-09-26|
|111|[linguishi/chinese_sentiment](https://github.com/linguishi/chinese_sentiment)|中文情感分析，CNN，BI-LSTM，文本分类|361|0|2022-02-10|
|111|[linguishi/chinese_sentiment](https://github.com/linguishi/chinese_sentiment)|中文情感分析，CNN，BI-LSTM，文本分类|363|0|2022-02-10|
|112|[hscspring/All4NLP](https://github.com/hscspring/All4NLP)|All For NLP, especially Chinese.|160|0|2021-10-22|
|113|[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）|36|0|2022-01-19|
|114|[W-Java/Population-Prediction](https://github.com/W-Java/Population-Prediction)|The future population of Singapore is predicted by SVM algorithm|15|0|2021-10-29|
|115|[lingjzhu/charsiu](https://github.com/lingjzhu/charsiu)|Charsiu: A neural phonetic aligner.|63|0|2022-02-12|
|116|[linbang/Metapath2vec](https://github.com/linbang/Metapath2vec)|使用DGL和pytorch实现metapath2vec|25|0|2021-09-17|
|117|[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|0|2022-02-17|
|117|[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|0|2022-02-18|
|118|[WHUFT/WHU_FinTech_Workshop](https://github.com/WHUFT/WHU_FinTech_Workshop)|武汉大学金融科技研讨班|44|0|2022-01-19|
|119|[01ly/Codes](https://github.com/01ly/Codes)|不可能不会系列|29|0|2022-02-10|
|120|[RenShuhuai-Andy/my-tools](https://github.com/RenShuhuai-Andy/my-tools)|my commonly-used tools|11|0|2021-11-29|
@ -129,7 +129,7 @@
|122|[evaseemefly/TyphoonSearchSys](https://github.com/evaseemefly/TyphoonSearchSys)|NMEFC——台风相似路径系统|10|0|2021-10-05|
|123|[Jackthebighead/duplicate-question-pair-identification](https://github.com/Jackthebighead/duplicate-question-pair-identification)|Three models are implemented for text similarity classification/STS problem on Quora Question Pairs dataset.|11|0|2021-11-12|
|124|[wx-chevalier/ai-models](https://github.com/wx-chevalier/ai-models)|Artificial Intelligence & Machine Learning & DeepLearning & NLP & CV Workbench 示例，算法，模型，应用，TensorFlow & PyTorch，Kaggle|18|0|2022-02-18|
|125|[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|42|0|2021-11-17|
|125|[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|0|2021-11-17|
|126|[JuliaCN/MeetUpMaterials](https://github.com/JuliaCN/MeetUpMaterials)|Julia中文社区活动的各种材料 Meetup Materials |61|0|2021-12-23|
|127|[Flowingsun007/DeepLearningTutorial](https://github.com/Flowingsun007/DeepLearningTutorial)|Talk is cheap,show me the code ! Deep Learning,Leaning deep,Have fun!|76|0|2022-02-10|
|128|[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 ...|51|0|2021-09-04|
@ -143,10 +143,10 @@
|136|[tinyms-ai/tinyms](https://github.com/tinyms-ai/tinyms)|Easy-to-Use deep learning development toolkit.|99|0|2022-02-14|
|137|[nmcdev/meteva](https://github.com/nmcdev/meteva)|提供气象产品检验相关程序|128|0|2021-12-16|
|138|[lvxingchang/Interesting-python](https://github.com/lvxingchang/Interesting-python)|-|49|0|2021-10-21|
|139|[polarisZhao/pytorch-cookbook](https://github.com/polarisZhao/pytorch-cookbook)|-|41|0|2022-01-13|
|139|[polarisZhao/pytorch-cookbook](https://github.com/polarisZhao/pytorch-cookbook)|-|42|0|2022-01-13|
|140|[xsthunder/download-youtube-subtitle](https://github.com/xsthunder/download-youtube-subtitle)|download youtube subtitles(closed caption, cc) as txt or json, support translation and proxy. available on PIP 🐍|31|0|2022-01-01|
|141|[xiaomingnotes/sdu2021](https://github.com/xiaomingnotes/sdu2021)|sdu2021 traffic交通监控|12|0|2021-11-03|
|142|[huseinzol05/malay-dataset](https://github.com/huseinzol05/malay-dataset)|Text corpus for Bahasa Malaysia, https://malaya.readthedocs.io/en/latest/Dataset.html|161|0|2022-02-15|
|142|[huseinzol05/malay-dataset](https://github.com/huseinzol05/malay-dataset)|Text corpus for Bahasa Malaysia, https://malaya.readthedocs.io/en/latest/Dataset.html|162|0|2022-02-15|
|143|[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|0|2021-12-13|
|144|[AnzorGozalishvili/unsupervised_keyword_extraction](https://github.com/AnzorGozalishvili/unsupervised_keyword_extraction)|Unsupervised approach to keyword extraction|15|0|2022-02-10|
|145|[lcan520/BankCardRecognition](https://github.com/lcan520/BankCardRecognition)|基于python3.6+opencv3+tensorflow+cnn的银行卡识别|13|0|2021-10-05|
@ -155,7 +155,7 @@
|148|[paudetseis/PlateFlex](https://github.com/paudetseis/PlateFlex)|Estimating effective elastic thickness of the lithosphere|19|0|2021-08-30|
|149|[xinihe/jrxy_python_course](https://github.com/xinihe/jrxy_python_course)|Python in Finance |53|0|2021-12-20|
|150|[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|0|2021-09-06|
|151|[hugo2046/Quantitative-analysis](https://github.com/hugo2046/Quantitative-analysis)|量化研究-券商金工研报复现|147|0|2022-02-12|
|151|[hugo2046/Quantitative-analysis](https://github.com/hugo2046/Quantitative-analysis)|量化研究-券商金工研报复现|148|0|2022-02-12|
|152|[Sanzo00/files](https://github.com/Sanzo00/files)|托管代码和一些文件|10|0|2021-11-28|
|153|[svakulenk0/KBQA](https://github.com/svakulenk0/KBQA)|Complex Question Answering over Knowledge Graphs|82|0|2022-02-11|
|154|[makelove/True_Artificial_Intelligence](https://github.com/makelove/True_Artificial_Intelligence)|真AI人工智能|40|0|2022-02-17|
@ -186,7 +186,7 @@
|179|[DeepTrial/Retina-VesselNet](https://github.com/DeepTrial/Retina-VesselNet)|A Simple U-net model for Retinal Blood Vessel Segmentation based on tensorflow2|219|0|2022-02-09|
|180|[simbafl/Data-analysis](https://github.com/simbafl/Data-analysis)|数据分析，挖掘建模。|157|0|2022-01-02|
|181|[zengwb-lx/yolov5-deepsort-pedestrian-counting](https://github.com/zengwb-lx/yolov5-deepsort-pedestrian-counting)|yolov5 + deepsort实现了行人计数功能， 统计摄像头内出现过的总人数，以及对穿越自定义黄线行人计数效果如下|45|0|2021-09-04|
|182|[tcmyxc/DL-AndrewNg](https://github.com/tcmyxc/DL-AndrewNg)|吴恩达深度学习2021年空白作业|15|0|2021-09-13|
|182|[tcmyxc/DL-AndrewNg](https://github.com/tcmyxc/DL-AndrewNg)|吴恩达深度学习2021年空白作业|16|0|2021-09-13|
|183|[blueapplehe/car_identify](https://github.com/blueapplehe/car_identify)|汽车识别，汽车车型识别，汽车品牌识别，车辆识别，深度学习，神经网络|92|0|2022-01-28|
|184|[lsh1994/remote_sensing_pretrained_models](https://github.com/lsh1994/remote_sensing_pretrained_models)|Remote Sensing pretrained weights with CNN finetune（PyTorch）|11|0|2021-09-17|
|185|[Ixiaohuihuihui/Tiny-Defect-Detection-for-PCB](https://github.com/Ixiaohuihuihui/Tiny-Defect-Detection-for-PCB)|This is a repository about PCB defect detection.|249|0|2022-02-10|
@ -194,17 +194,17 @@
|187|[KoichiYasuoka/SuPar-Kanbun-1.3.4](https://github.com/KoichiYasuoka/SuPar-Kanbun-1.3.4)|Tokenizer POS-tagger and Dependency-parser for Classical Chinese|14|0|2021-12-16|
|188|[lures2019/lures2020-demos](https://github.com/lures2019/lures2020-demos)|lures2020年写的一些项目和程序|26|0|2021-09-11|
|189|[feng-li/Distributed-Statistical-Computing](https://github.com/feng-li/Distributed-Statistical-Computing)|Teaching Materials for Distributed Statistical Computing (大数据分布式计算教学材料)|80|0|2022-02-08|
|190|[EMUNES/Auto-Subtitle-File-Generation](https://github.com/EMUNES/Auto-Subtitle-File-Generation)|Generate subtitle files with timelines in an automatic way.|24|0|2021-11-09|
|191|[arjunmann73/Data-Analytics-Projects](https://github.com/arjunmann73/Data-Analytics-Projects)|:mag_right: Data analysis with real world data sets using Python :mag:|94|0|2021-10-16|
|192|[HuichuanLI/Recommand-Algorithme](https://github.com/HuichuanLI/Recommand-Algorithme)|推荐算法实战(Recommend algorithm)|35|0|2021-10-31|
|193|[moeheart/jx3bla](https://github.com/moeheart/jx3bla)|JX3 Battle Log Analyse|10|0|2021-12-06|
|194|[zll17/Neural_Topic_Models](https://github.com/zll17/Neural_Topic_Models)|Implementation of topic models based on neural network approaches.|227|0|2021-11-12|
|195|[SocratesAcademy/datascience](https://github.com/SocratesAcademy/datascience)|Introduction to Python Programming for Data Science|30|0|2022-01-13|
|196|[collective-action/tech](https://github.com/collective-action/tech)|Documentation of all collective action from tech workers.|186|0|2022-02-18|
|197|[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|39|0|2022-02-09|
|198|[leolle/deep_learning](https://github.com/leolle/deep_learning)|projects about NLP knowledge graph, web crawling, word embedding, entity&relation extraction.|11|0|2021-11-10|
|199|[zhaihulu/DataScience](https://github.com/zhaihulu/DataScience)|-|20|0|2021-10-12|
|200|[chengjun/mybook](https://github.com/chengjun/mybook)|My Lectures on Computational Communication |23|0|2022-01-13|
|190|[codecat0/CV](https://github.com/codecat0/CV)|本仓库将使用Pytorch框架实现经典的图像分类网络、目标检测网络、图像分割网络，图像生成网络等，并会持续更新！！！|14|0|2022-01-01|
|191|[EMUNES/Auto-Subtitle-File-Generation](https://github.com/EMUNES/Auto-Subtitle-File-Generation)|Generate subtitle files with timelines in an automatic way.|24|0|2021-11-09|
|192|[arjunmann73/Data-Analytics-Projects](https://github.com/arjunmann73/Data-Analytics-Projects)|:mag_right: Data analysis with real world data sets using Python :mag:|94|0|2021-10-16|
|193|[HuichuanLI/Recommand-Algorithme](https://github.com/HuichuanLI/Recommand-Algorithme)|推荐算法实战(Recommend algorithm)|35|0|2021-10-31|
|194|[moeheart/jx3bla](https://github.com/moeheart/jx3bla)|JX3 Battle Log Analyse|10|0|2021-12-06|
|195|[zll17/Neural_Topic_Models](https://github.com/zll17/Neural_Topic_Models)|Implementation of topic models based on neural network approaches.|227|0|2021-11-12|
|196|[SocratesAcademy/datascience](https://github.com/SocratesAcademy/datascience)|Introduction to Python Programming for Data Science|30|0|2022-01-13|
|197|[collective-action/tech](https://github.com/collective-action/tech)|Documentation of all collective action from tech workers.|186|0|2022-02-19|
|198|[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|39|0|2022-02-09|
|199|[leolle/deep_learning](https://github.com/leolle/deep_learning)|projects about NLP knowledge graph, web crawling, word embedding, entity&relation extraction.|11|0|2021-11-10|
|200|[zhaihulu/DataScience](https://github.com/zhaihulu/DataScience)|-|20|0|2021-10-12|
<div align="center">
<p><sub>↓ -- 感谢读者 -- ↓</sub></p>