There are 13 repositories under toxic-comment-classification topic.
An R wrapper for Conversation AI's Perspective API
Kaggle: Quora Insincere Questions Classification - detect toxic content to improve online conversations
Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis
在Pytorch下,采用LSTM/C-LSTM/CNN等方法,对评论进行多标签分类
A web-app to identify toxic comments in a youtube channel and delete them.
Kaggle Competition: Toxic Comments Classification (Link: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge)
AntiToxicBot is a bot that detects toxics in a chat using Data Science and Machine Learning technologies. The bot will warn admins about toxic users. Also, the admin can allow the bot to ban toxics.
Collection of Deep Learning Text Classification Models in Keras; Includes a GPU tutorial.
Deep Learning for Toxic Comment Classification
Набор ноутбуков, в которых решаются различные задачи обработки естественного языка (NLP).
The official code to reproduce results from the NACCL2019 paper: White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks
From Hero to Zéroe: A Benchmark of Low-Level Adversarial Attacks
This GitHub repository provides an implementation of the paper "MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network" . MAGNET is a state-of-the-art approach for multi-label text classification, leveraging the power of graph neural networks (GNNs) and attention mechanisms.
A discord bot capable of detecting toxic messages sent to a server, delete them and warn the author.
A basic and simple yet powerful Python library to detect toxicity/profanity of a review or list of reveiws.
NLP deep learning model for multilingual toxicity detection in text 📚
Familiarity with some cloud services
Open source discord moderation bot leveraging NLP with a focus on explainability.
:3rd_place_medal: (Bronze medal - 100th place - Top 7%) Repository for the "Jigsaw Multilingual Toxic Comment Classification" Kaggle competition.
Toxic content classification using Deep Learning Pytorch
Репозиторий python-пакета "toxicity". Выявление токсичного контента в русскоязычных текстах c помощью глубокого обучения.
Final Project of the Data Science postgraduate class at MDCC/UFC
Comments & Twitter accounts gRPC classification service.
Identify and classify toxic commentary
Recurrent Capsule Network for Text Classification
This repository contains the system description and the codes that we implemented for participating in EACL-2024 Shared Task-5.
Total Surveillance for Infiltrators, a defense security solutions suite, sort documents on the fly for malcontent, configure drones for maximum area coverage, send communications via commo hubs, protected by swarm and blockchain. TLDR : Automated Solutions for Counter Insurgency. This repo contains the AI/ML models.
Natural Language Processing: A multi-headed model capable of detecting different types of online discussion toxicity like threats, obscenity, insults, and identity-based hate using Keras RNN LSTM and focal loss to address a hyper-imbalanced dataset.
Toxic-Comment-Classifier
Bert Classification on Jigsaw Data with Gender as a basic genre, followed by identifying Bias in Toxic Classification.
Detecção de comentários ou textos preconceituosos com processamento de linguagem natural. Projeto apresentado ao Curso de Especialização Lato sensu de Inteligência Artificial e Aprendizado de Máquina da Universidade Nove de Julho.
Twitter Account | Sentimental Analysis
The Toxic Comment Classification project is an application that uses deep learning to identify toxic comments as toxic, severe toxic, obscene, threat, insult, and identity hate based using various NLP algorithm