JeffAzure's Stars
astaxie/build-web-application-with-golang
A golang ebook intro how to build a web with golang
DIYgod/RSSHub
🧡 Everything is RSSible
zenorocha/clipboard.js
:scissors: Modern copy to clipboard. No Flash. Just 3kb gzipped :clipboard:
networkx/networkx
Network Analysis in Python
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.
chenyuntc/pytorch-book
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
billryan/resume
An elegant \LaTeX\ résumé template. 大陆镜像 https://gods.coding.net/p/resume/git
iamseancheney/python_for_data_analysis_2nd_chinese_version
《利用Python进行数据分析·第2版》
CavsZhouyou/Front-End-Interview-Notebook
:ant:前端面试复习笔记
plotly/falcon
Free, open-source SQL client for Windows and Mac 🦅
doramart/DoraCMS
DoraCMS是基于Nodejs+eggjs+mongodb编写的一套内容管理系统，结构简单，较目前一些开源的cms，doracms易于拓展，特别适合前端开发工程师做二次开发。
liyupi/sql-generator
🔨 用 JSON 来生成结构化的 SQL 语句，基于 Vue3 + TypeScript + Vite + Ant Design + MonacoEditor 实现，项目简单（重逻辑轻页面）、适合练手~
girls-in-ai/Girls-In-AI
免费学代码系列：小白python入门、数据分析data analyst、机器学习machine learning、深度学习deep learning、kaggle实战
hua1995116/react-resume-site
木及简历，一款markdown的在线简历工具。 https://www.mujicv.com
anyant/rssant
蚁阅 - 让 RSS 更好用，轻松订阅你喜欢的博客和资讯
thunlp/TAADpapers
Must-read Papers on Textual Adversarial Attack and Defense
villeheikkila/fullstackopen
Exercises for the Full Stack Open course.
wen-fei/seu-thesis-latex-template
东南大学毕业论文latex模板
sfzhou5678/TextualAdversarialAttack-Tianchi
天池竞赛安全AI挑战者计划第三期 - 文本分类对抗攻击 线上排名12/1175 &“最佳奇思妙想奖”
lamer112311/Dnnme2
New version of telegram deanonymization bot
xiaochaohit/C-plus
《数据结构、算法与应用》C++描述，课本代码及课后习题代码
joe817/Name-Disambiguation-Biendata-
2019 Biendata竞赛平台“OAG–WhoIsWho 同名消歧竞赛 赛道一”消歧比赛，第一名解决方案
ViliamV/stylometry
Sample project for using stylometry to deanonymize Twitter account author.
gechengze/nlp-notebook
nlp常见模型，常见任务简单demo
MurenMurenus/CookieDeanonymization
A model to recognize gender and age of cookie's owner.
sraashis/graph-de-anonymization
Seed based and seed-free graph de-anonymization.
abigailbarnes/Deanonymizing-Datasets
Project designed to deanonymize a given dataset by matching the pseudonymous user IDs in the Last.fm dataset with the names on a non-anonymous music website
bhargavmuppalla/Seed-Based-Deanonymization
Seed-based-deanonymization is an attack to deanonymize the data. which is identifying the personal information from non-personal data.
michellepistner/SoDA_Deanonymization
Project code for SoDA 502 Reddit author attribution project
reallyahmed/Graph-Deanonymization
Utilize graph anonymization algorithms to solve seed based de-anonymization. In the seed based de-anonymization dataset, there are two graph files (G1.edgelist and G2.edgelist) and a seed node pairs file. The graphs are given in edgelist filetype. Each row in G*.edgelist represents an edge connecting two nodes. For example, the first row in G1.edgelist <0 330> means there is an edge between node 0 and node 330 in Graph 1. The seed node pairs file (seed_node_pairs.txt) gives some matched node seed pairs. In the file seed_node_pairs.txt, the first column refers the node number in G1 and the second column refers the node number in G2. For example, in the first row of seed_node_pairs.txt, <0 3389> means the node 0 in Graph 1 is mapped to node 3389 in Graph 2. Given those mapped seed pairs in seed_node_pairs.txt and two graphs, the project outputs the full nodes pairs between Graph 1 and Graph 2.