Kaggle新赛(baseline)-基于BERT的fine-tuning方案+基于tensor2tensor的Transformer Encoder方案

4th Place Solution for Kaggle Competition: Quora Insincere Questions Classification

Kaggle: Quora Insincere Questions Classification - detect toxic content to improve online conversations

This repository contains code to Quora Insincere Questions classification using KerasNLP

45th Place Solution of the Quora insincere questions classification competition in Kaggle.

Solutions of the Kaggle competition: Quora Insincere Questions Classification

The Quora Insincere Question Classification competition allows us to use the four embeddings: glove.840B.300d (GloVe), paragram_300_sl999 (paragram), wiki-news-300d-1M (wiki) and GoogleNews-vectors-negative300 (GoogleNews). In a kernel titled: "How to: Preprocessing when Using Embeddings", the author raises the issue of tokenization and its effect on how much of the training vocabulary is covered by words in an embedding. The author uses Google news embeddings to illustrate this point. In this kernel I expand on this point by exploring the effect of tokenization assumptions on the other three embeddings: GloVe, Paragram, and Wiki News.

短文本分类，基于pytorch

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Using a GRU-Attention-Capsule network to automatically detect insincere questions

Solution for Kaggle's Quora Insincere Questions Classification competition

Detect toxic content to improve online conversations

In this competition, Kagglers will develop models that identify and flag insincere questions. To date, Quora has employed both machine learning and manual review to address this problem. With your help, they can develop more scalable methods to detect toxic and misleading content.

Quora Insincere Questions Classification using NLP-BERT Model trained on imbalanced dataset [demo video]

This repository contains my approach to Quora Insincere Questions Classification Competition hosted on Kaggle

This project, detecting toxic content to improve online conversations, is my Kaggle competition. I got a bronze medal in the top 6% from 4037 teams.

Kaggle competition- colab notebook

A text classification task using Deep Learning

This project focuses on classifying insincere questions using machine learning and transformer models. Advanced NLP preprocessing techniques were applied to prepare the data, followed by the integration of Stanford GloVe embeddings to increase vocabulary coverage. The models were then trained and evaluated to ensure robust performance.

53rd Place Solution for Quora Insincere Questions Classification on Kaggle

59th place solution (top 2%)

This is repository is for solutions for [quora-insincere-questions](https://www.kaggle.com/c/quora-insincere-questions-classification)

5th place solution in Quora insincere question classification

Bidirectional LSTM text classification using Tensorflow 2 GPU for Quora Insincere Questions Classification competition on Kaggle

We are going to improve the quality of discussions on Quora platform by detecting toxic content. Specifically, we want to build a predictive NLP model that labels questions asked on Quora as either sincere or insincere.

This repository contains Natural Language Processing Projects like Sarcasm Detection, Quora Insincere Questions Classification & Edgar Sentiment Analysis

Quora Insincere Questions Classification

Quora insincere questions classification

Quora Insincere Questions Classification

Quora Insincere Questions Classification