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As the digital world grows, so does the challenge of moderating online conversations. Toxic comments- those that are harmful, offensive, or…

Sep 25, 2024 · 4 min read · 3 claps #ai #machine-learning #nlp

AI

This article aims to perform predictive analysis, using the dataset available from Kaggle, to identify instances of toxic content within…

Mar 27, 2024 · 11 min read · 8 claps #multilabel-classification #logistic-regression #random-forest

Introduction

Aug 19, 2023 · 5 min read · 57 claps #toxic-comment #machine-learning #ai

Disclaimer: This article explores the Perspective API for online toxic comments predictions. Some toxic comments shown in this article are…

Jul 12, 2022 · 22 min read · 1 claps #data-science #toxic-comment #lgbtq

Text data is available everywhere and due to its unstructured nature, it becomes difficult and time consuming to extract information from…

Mar 22, 2021 · 11 min read · 6 claps #text-classification #multi-label #toxic-comment

Freedom of expression of various points of view, including toxic, aggressive, and abusive comments, might have a long-term negative…

Oct 25, 2020 · 10 min read · 83 claps #machine-learning #neural-networks #social-media

AI HUM

I’ve recently participated in a Kaggle’s competition ‘Multilingual Toxicity Comment Classification’ sponsored by The Conversation AI team…

Jun 18, 2020 · 5 min read · 50 claps #machine-learning-ai #artificial-intelligence #toxic-comment

AI

이번 글에서는 Scikit-Learn을 이용해서 악성(Toxic)문장을 분류하는 분류기를 만들고, Lime을 이용해 분류기의 결과를 분석해서 문장의 어떤 단어가 분류결과에 영향을 미쳤는지 알아보려고 합니다. 이를 통해 악성으로 분류하는데 큰 영향을…

May 10, 2020 · 10 min read · 2 claps #lime #xai #toxic-comment