Source code for ISPRAS-2021 journal paper "Language Models Application in Sentiment Attitude Extraction Task" (in Russian)

Fine tuning de modèle de pré-entrainement BERT pour classification des sentiments des commentaires des clients

Here are some notes of learning and common codes

A web server to host Google BERT trained model

Identify and classify toxic online comments,based on kaggle dataset

An analysis model that classifies twitter tweets using BERT and Tensor Flow libraries.

The semantic volatility of neologisms.

University project on Deep Learning

Multi-Label Classification using BERT and XLNet

Created a robust method to prioritize reviews and evaluate responses by extracting the emotion associated with the review using deep learning models.

Developed a machine learning algorithm using Bidirectional Encoder Representations from Transformers (BERT) for email spam detection

In this Machine Learning project, I harness the power of advanced algorithms to effectively categorize resumes found within a specified directory. Through an intricate analysis of their content, the script automates the process of sorting these resumes, thereby enhancing and streamlining the hiring process. 🚀

Text summarising is the process of producing a brief, coherent summary of a text while keeping its essential details and primary concepts.

Ensemble Network Including Transformer Models for NLP Patient Text and ED Visit Prediction

Attempt to use BERT pre-trained model fine-tuned for medical purposes to classify various symptoms

ALBERT and DistilBERT classification models for the DBpedia ontology dataset.

Repository for a Django App to classify NEWS articles headlines into various topics using BERT.

NLP - CS4120 @ Northeastern University | Final Project | Performing emotion classification on a kaggle dataset using models such as Logistic Regression, LSTM Neural Network, and DistilBERT, a transform-based model.

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.