Unsupervised sentiment analysis of Tweets (Machine Learning @ EPFL)

Idea is to develop an approach that given a sample will identify the sub themes along with their respective sentiments.

Creation of a web app where users can take pictures of their receipts and receive information on the calories of the items in the receipt. Project for HackNYU_2020.

Machine Translation

Jupyter Notebooks consisting of various nlp tasks. (NLP role based interviews)

🏷️ Classificação multi-label com BERT.

Application of the BERT model for text classification

BERT-Sentiment-Analysis AI Model

Sentiment Analysis on the Corona Tweet Dataset. Classification of tweets into classes: Positive, Negative and Neutral using various Machine Learning Models and Pre-Trained Models such as BERT and RoBERTa.

4th place project made for Ohio State University's HackAI hackathon 2022. Uses Bert Vectorization/Tfidf to classify text segments to determine if a text selection contains opinionated of false information

A BERT model built with PyTorch.

Model that demonstrates in forecasting the Length dimension of a Product

This is the official implementation of our paper Robust Hate Speech Detection via Mitigating Spurious Correlations (Tiwari et al., AACL-IJCNLP 2022)

Machine Learning & Deep Learning Algorithms

Building an IT help desk system using BERT

This project focuses on improving customer satisfaction through sentiment analysis of customer feedback for an app designed for online classes and video conferencing. The objective is to analyze customer sentiments expressed in their feedback and gain insights to enhance the user experience and address any pain points.

end of 2nd year of engineering project

An NLP Project using BERT model for Tweeter similarity analysis

We were intended to deeply analysis sentiment or reviews. We have used BeautifulSoup4 to Scrape data from 'Yelp' and used 'bert-base-multilingual-uncased model' finetuned for sentiment analysis.