zyz135246

pytorch_fake_news_Classification_mml

使用pytorch完成的一个多模态分类任务，文本和图像部分分别使用了bert和resnet提取特征（在config里可以组合多种模型）,在我的小规模数据集上取得了良好的性能（验证集acc96%）

mixup-text

Exploring mixup strategies for text classification

SimpleClassification

Simple Text Classification[WIP]

attack_train

paper

TextCRS

Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks (IEEE S&P 2024)

adversarial_DGA

new-pac

科学上网/自由上网/翻墙/软件/方法，一键翻墙浏览器，免费shadowsocks/ss/ssr/v2ray/goflyway账号，vps一键搭建脚本/教程

icc2022

CharBot-The-Domain-Generation-Algorithms-

DGA-Generated_Random_Domain_Name_Detection_Based_on_BiLSTM

SemAttack

[NAACL 2022] "SemAttack: Natural Textual Attacks via Different Semantic Spaces" by Boxin Wang, Chejian Xu, Xiangyu Liu, Yu Cheng, Bo Li

TextAttack

TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/

Chinese-Text-Classification-Pytorch

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

PICCOLO

fanci

FANCI is a prototype implementation of a machine learning based classification engine for non-existent domains to detect domain gernation algorithm malware traffic.

BITE

Code and data for paper "BITE: Textual Backdoor Attacks with Iterative Trigger Injection"

TAADpapers

Must-read Papers on Textual Adversarial Attack and Defense

CSE544T-Project-TextBugger

StyleAttack

Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer"

Lhy_Machine_Learning

李宏毅2021/2022/2023春季机器学习课程课件及作业

DeepDGA

Implementation of 《DeepDGA: Adversarially-Tuned Domain Generation and Detection》 arXiv:1610.01969

DomainGAN

Paper Implementation of DomainGAN: Generating Adversarial Examples to Attack Domain Generation Algorithm Classifiers

LSTM-MI

LSTM-MI (Multiclass Imbalance) for DGA Detection

Random-forest-Masked-N-grams

Random forest Masked N-grams for DGA detection

books

【编程随想】收藏的电子书清单（多个学科，含下载链接）

Mirai-PKDGA-Code

PKDGA

competition-baseline

数据挖掘、计算机视觉、自然语言处理、推荐系统竞赛知识、代码、思路

text_classification

使用rnn,lstm,gru,fasttext,textcnn,dpcnn,rnn-att,lstm-att,兼容huggleface/transformers，以及以transforemrs作为词嵌入模型，后面接入cnn、rnn、attention等等做文本分类。以及各个模型的对比