This is the second project to be completed in Upskill ISA Intelligent Machines. The project was done after the end of the competition. The ensemble of BERT, GPT2, XLNet was used in this model that obtained 0.94656 private scores on Kaggle.

Implemented SOTA model for fine tuning our tweet and Reddit data for Prediction of Rumour through SDQC

👨‍🎓 This repo is a supplement to my video on Transformers and Text Summarization as part of my series AI does AI (https://youtu.be/p_6xgrykPMQ)

A NLP question answering service leveraging user reviews

Experiments for Google Quest QA Labeling kaggle competition

Multi-Label Classification using BERT and XLNet

This repository houses three fine-tuned machine learning models for NLP tasks: Text Emotion Recognition, Sentiment Analysis, and Cyberbullying Detection.

Django application of https://github.com/Tikquuss/eulascript, the Machine learning (ML) solution that review end-user license agreements (EULA) for terms and conditions that are unacceptable to the government

XLNet: Generalized Autoregressive Pretraining for Language Understanding

Dash-based GUI for testing text classification with NLP models like BERT, RoBERTa, XLNet, etc.

Some experiments to compare the performances of some pre-trained transformer models on a basic sentiment regression task

invos Data Project - https://www.youtube.com/watch?v=uSjCmNSwtIo

a novel hypernym discovery system based on XLNet, which outperformed baselines in SemEval tasks, highlighting expertise in innovative language models and ethical considerations in NLP.

Simple from-scratch implementations of transformer-based models that match the state of the art.

Detecting fake news online with an ensemble approach to deep learning algorithms

Affevtive Bias in Large Pre-trained Language Models

Exploring a collection of Jupyter notebooks showcasing a variety of Natural Language Processing (NLP) projects.

We have proposed a multimodal approach. Where we first took the best unimodal for textual and visual data classification by testing and automation process. Then we fusion of the two models which can successfully classify the materials that have been damaged using the image and text data. EfficientNetB3+BERT multimodal better accuracy with 94.18%

2023년 인공지능 온라인 경진대회 - 전북대학교 SW중심대학사업단

Google Colab based on a fork of REMI repo. Try this incredible REMI Pop Music Transformer easily and quickly :)