A code solution to the Kaggle competition by using basic classifications techniques.
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Updated
Oct 18, 2020 - Jupyter Notebook
A code solution to the Kaggle competition by using basic classifications techniques.
Toxic comment classification using Tensorflow and react.js
Applies probability based bag-of-words model for toxicity classification of social media texts
Machine learning pipeline for predicting molecular toxicity.
Atividade prática de Redes Neurais
A repo for the EWC artifical Neural network model for predicting EC3 Values For Skin Sensitization
基于SparseEA的特征选择方法在毒性分类中的应用
Putting together VS Code extension, express, tensorflow.js, and a text toxicity classifier into a simple project.
Identification and Classification of Toxic comments using Machine Learning
Model that determines the level of toxicity of Russian and English messages
Building Model to for analysis sentiment on social media ,marketplace, customer review etc.
Full stack application for annotating video game matches. Used for https://github.com/TheBv/toxic-video-games-gnn
In this project we have tried to do multi-label hate-speech classification in Bengali and Hindi language using fill-mask transformer models.
Classifying various toxic comments using DistilBert
This repository makes available a new dataset for toxicity detection in Brazilian Portuguese from the work accepted by the 16th International Conference on Computational Processing of Portuguese (PROPOR 2024). The data collected is from the most popular Brazilian subreddits in 2022.
Build a model to identify toxic statements and reduce bias in classification
The repo contains notebooks for the Jigsaw Unintend Bias in Toxicity Classification contest hosted on Kaggle
This repo contains code for toxic comment classification using deep learning models based on recurrent neural networks and transformers like BERT. The goal is to detect and classify toxic comments in online conversations using Jigsaw's Toxic Comment Classification dataset.
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