A basic NLP project on musical instruments reviews on Amazon.

Implementing VADER, RoBERTa and TextCNN on a twitter dataset from Kaggle

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.

LayoutLMv3 applied to a VQA problem with infographics.

Natural language processing (NLP) is a branch of artificial intelligence (AI) that enables computers to comprehend, generate, and manipulate human language. Natural language processing has the ability to interrogate the data with natural language text or voice.

More and more people are exchanging text messages through the use of social media, and the analysis of the information can be used to make statistics in the behavior and in people's psychology. Using Natural Language Processing (NLP), we can extrapolate key words from each message that allow us to achieve the proposed goals.

This repository implements a question-answering system using Gradio's lower-level API, featuring two input fields for context and user questions. The system utilizes the deepset/roberta-base-squad2 model and provides a user-friendly interface for model interaction.

This is NLP project of text multi-classification. My pre-trained model classify speech into three different categories offensive, hateful and neither.

Sentiment Analysis using roBERTa

Este projeto utilizou a API do Twitter para coletar cerca de 50.000 tweets sobre "The Last of Us" e, em seguida, aplicou técnicas de pré-processamento de texto, Word Cloud e análise de sentimento utilizando o modelo pré-treinado Roberta.

This repository contains assignments, the final course project, and the project work assigned for the Natural Language Processing (NLP) course within the Artificial Intelligence Master's program.

Projekt u sklopu predmeta Obrada prirodnog jezika

- Sentiment Analysis classifier of amazon customer reviews

A Windows desktop test app made using flutter for testing the sentiment analysis model.

Building a multilingual NER app with HuggingFace, Gradio and Comet

This repository aimed at building your own Speech classifier as well. This will enable an idea where human natural language is understood and classified in one of the category based on the context of the text spoken by the human.

Building this project to generate MCQ Questions from any type of text and generate answers and distractors for it.

Sentiment analysis of short reviews of any letterbox's list using the state-of-the-art machine learning model RoBERTa with PyTorch.