Multiclass classification on tweets about the coronavirus

A Deep Learning Based Voice Analytics toolkit

We explored recent studies in Question Answering System. Then tried out 3 different QA models(BERT and DistilBERT) for the sake of learning.

Fine tuning pre-trained transformer models in TensorFlow and in PyTorch for question answering

This paper describes Humor Analysis using Ensembles of Simple Transformers, the winning submission at the Humor Analysis based on Human Annotation (HAHA) task at IberLEF 2021.

Positive/negative sentiment model on cleaned text data using Distilbert NLP pre-trained model from Hugging Face

Finetuning DistilBERT on IMDB Dataset

This repository contains my work on the prevention and anonymization of dox content on Twitter. It contains python code and demo of the proposed solution.

Using Bert and Distilbert to fill in the gaps

Performing named entity extraction task using Huggingface Transformers

Sentiment analysis on products reviews with Vader and Distilbert

Developing a feedback theory-informed natural language processing (NLP) model to enable large-scale evaluation of written feedback, and analysing a large set of feedback extracted from Moodle using this model to understand the presence of student-centred feedback elements, the commonality and differences in feedback provision across disciplines.

This project centers on elevating customer satisfaction by conducting sentiment analysis on customer feedback for an online classes and video conferencing app. The aim is to decipher customer sentiments in their feedback, extract insights, and improve user experience while addressing any concerns.

Finetune the Transformer model 'DistilBERT' with PyTorch framework . Then inference on a dataset by using this fine-tuned model with the help of Pipeline.

Implemented pre-trained Transformer-based distilBERT and BERT multilingual model to classify sentiments in positive or negative class and ranked them on scale of 1 to 5

This app searches reddit posts and comments to determine if a product or service has a positive or negative sentiment and predicts top product mentions using Named Entity Recognition

The official repository for the PSYCHIC model

Aim to build a question- answering product that can that can understand the information in these articles and answer some simple questions related to those articles.