Wednesday, March 3Digital Marketing Journals

eda

Hands-on for Toxicity Classification and minimization of unintended bias for Comments using classical machine learning models | by Anurag Maji
ai bot, ai chat, ai chatbot, best chatbot, chatbot, chatbot ai, chatbot app, chatbot online, chatbot website, classification-algorithms, conversation with ai, creating chatbots, eda, kaggle-competition, machine-learning, nlp, robot chat

Hands-on for Toxicity Classification and minimization of unintended bias for Comments using classical machine learning models | by Anurag Maji

In this blog, I will try to explain a Toxicity polarity problem solution implementation for text i.e. basically a text-based binary classification machine learning problem for which I will try to implement some classical machine learning and deep learning models.For this activity, I am trying to implement a problem from Kaggle competition: “Jigsaw Unintended Bias in Toxicity Classification”.In this problem along with toxicity classification, we have to minimize the unintended bias (which I will explain briefly in the initial section).sourceBackground:This problem was posted by the Conversation AI team (Research Institution) in Kaggle competition.This problem’s main focus is to identify the toxicity in an online conversation where toxicity is defined as anything rude, disrespectful, or o...