Implementing VADER, RoBERTa and TextCNN on a twitter dataset from Kaggle
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Updated
May 23, 2024 - Jupyter Notebook
Implementing VADER, RoBERTa and TextCNN on a twitter dataset from Kaggle
A basic NLP project on musical instruments reviews on Amazon.
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.
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.
LayoutLMv3 applied to a VQA problem with infographics.
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
For this project, machine learning algorithms are used on amazon fine food reviews dataset to analyze if the given review is a positive review or a negative review.
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.
Finetuning Roberta on your own dataset
A Windows desktop test app made using flutter for testing the sentiment analysis model.
Building a multilingual NER app with HuggingFace, Gradio and Comet
Sentilyze aims to analyze sentiment in text from social media, news, and websites. Real-time analysis, granular classification, customizable settings.
This repository contains the code, models and corpus of the project "Generative Adversarial Networks for Text-to-Image Synthesis & Generation: A Comparative Analysis of Natural Language Processing models for the Spanish language".
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