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<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>
# 中文新星榜 > 软件类 > Jupyter Notebook
<sub>数据更新: 2021-12-23&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: 2021-12-24&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|Created|
|:-|:-|:-|:-|:-|:-|
|1|[yangxy/GPEN](https://github.com/yangxy/GPEN)|-|769|2021-12-21|2021-04-07|
|2|[4paradigm/AutoX](https://github.com/4paradigm/AutoX)|AutoX is an efficient automl tool, which is mainly aimed at data mining competitions with tabular data.|331|2021-12-20|2021-07-21|
|3|[d2l-ai/d2l-zh-pytorch-slides](https://github.com/d2l-ai/d2l-zh-pytorch-slides)|Pytorch版代码幻灯片|252|2021-12-22|2021-02-04|
|4|[luo3300612/Visualizer](https://github.com/luo3300612/Visualizer)|assistant tools for attention visualization in deep learning|186|2021-08-11|2021-08-09|
|1|[yangxy/GPEN](https://github.com/yangxy/GPEN)|-|772|2021-12-21|2021-04-07|
|2|[4paradigm/AutoX](https://github.com/4paradigm/AutoX)|AutoX is an efficient automl tool, which is mainly aimed at data mining competitions with tabular data.|334|2021-12-23|2021-07-21|
|3|[d2l-ai/d2l-zh-pytorch-slides](https://github.com/d2l-ai/d2l-zh-pytorch-slides)|Pytorch版代码幻灯片|253|2021-12-23|2021-02-04|
|4|[luo3300612/Visualizer](https://github.com/luo3300612/Visualizer)|assistant tools for attention visualization in deep learning|189|2021-08-11|2021-08-09|
|5|[44670/SourceHanSans-Pixel](https://github.com/44670/SourceHanSans-Pixel)|基于思源黑体的开源像素字体|170|2021-08-20|2021-08-18|
|6|[chokkan/mlnote](https://github.com/chokkan/mlnote)|機械学習帳|160|2021-12-17|2021-09-29|
|6|[chokkan/mlnote](https://github.com/chokkan/mlnote)|機械学習帳|168|2021-12-22|2021-09-29|
|7|[datawhalechina/thorough-pytorch](https://github.com/datawhalechina/thorough-pytorch)|-|114|2021-11-15|2021-07-31|
|8|[davidfrz/yolov5_distance_count](https://github.com/davidfrz/yolov5_distance_count)|使用yolov5，双目摄像头进行测距|99|2021-07-16|2021-07-10|
|9|[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|96|2021-11-17|2021-11-04|
@ -21,9 +21,9 @@
|14|[lingjzhu/charsiu](https://github.com/lingjzhu/charsiu)|Charsiu: A neural phonetic aligner.|44|2021-12-20|2021-08-29|
|15|[RuifMaxx/Multidimensional-time-series-with-transformer](https://github.com/RuifMaxx/Multidimensional-time-series-with-transformer)|transformer/self-attention for Multidimensional time series forecasting 使用transformer架构实现多维时间预测|42|2021-08-10|2021-07-16|
|16|[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|42|2021-09-04|2021-01-30|
|17|[ni1o1/transbigdata](https://github.com/ni1o1/transbigdata)|A Python package developed for transportation spatio-temporal big data processing, analysis and visualization.|41|2021-12-18|2021-10-21|
|18|[jonatasgrosman/wav2vec2-sprint](https://github.com/jonatasgrosman/wav2vec2-sprint)|-|41|2021-06-08|2021-03-22|
|19|[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 ...|39|2021-09-04|2021-03-28|
|17|[ni1o1/transbigdata](https://github.com/ni1o1/transbigdata)|A Python package developed for transportation spatio-temporal big data processing, analysis and visualization.|41|2021-12-23|2021-10-21|
|18|[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 ...|41|2021-09-04|2021-03-28|
|19|[jonatasgrosman/wav2vec2-sprint](https://github.com/jonatasgrosman/wav2vec2-sprint)|-|41|2021-06-08|2021-03-22|
|20|[boyu-ai/Hands-on-RL](https://github.com/boyu-ai/Hands-on-RL)|https://hrl.boyuai.com/|38|2021-08-14|2021-08-08|
|21|[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|33|2021-08-28|2021-04-18|
|22|[DIUx-xView/xview3-reference](https://github.com/DIUx-xView/xview3-reference)|Reference data processing code and model for the xView3 prize challenge.|30|2021-11-29|2021-08-31|
@ -35,8 +35,8 @@
|28|[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, AutoInt, FiBiNet,DIN, DIEN ... （pytorch, tf2.0）|22|2021-12-07|2021-07-08|
|29|[buzhidaoshenme/YOLOX-OBB](https://github.com/buzhidaoshenme/YOLOX-OBB)|YOLOX in DOTA with KLD loss. (Oriented Object Detection)（Rotated BBox）基于YOLOX的旋转目标检测|21|2021-11-19|2021-09-18|
|30|[accomdemy/accomdemy](https://github.com/accomdemy/accomdemy)|Welcome to Accomdemy! 歡迎來到伴伴學！|21|2021-12-22|2021-05-11|
|31|[yijixiuxin/chanlun](https://github.com/yijixiuxin/chanlun)|基于缠中说禅所理解的市场行情的分析工具|19|2021-12-18|2021-12-10|
|32|[kzbkzb/Python-AI](https://github.com/kzbkzb/Python-AI)|我的文章记录|19|2021-12-17|2021-10-18|
|31|[kzbkzb/Python-AI](https://github.com/kzbkzb/Python-AI)|我的文章记录|20|2021-12-17|2021-10-18|
|32|[yijixiuxin/chanlun](https://github.com/yijixiuxin/chanlun)|基于缠中说禅所理解的市场行情的分析工具|19|2021-12-18|2021-12-10|
|33|[PaddlePaddle/PaddleSpatial](https://github.com/PaddlePaddle/PaddleSpatial)|PaddleSpatial is an open-source spatial-temporal computing tool based on PaddlePaddle. |19|2021-12-17|2021-07-12|
|34|[EMUNES/Auto-Subtitle-File-Generation](https://github.com/EMUNES/Auto-Subtitle-File-Generation)|Generate subtitle files with timelines in an automatic way.|19|2021-11-09|2021-02-15|
|35|[chokkan/python](https://github.com/chokkan/python)|Python早見帳|17|2021-11-28|2021-10-04|