Abstract: The article suggests an understandable and lean multi-class text classification grounded in standard natural language processing (NLP) techniques along with the introduction of supervised ...

The successful application of large-scale transformer models in Natural Language Processing (NLP) is often hindered by the substantial computational cost and data requirements of full fine-tuning.

This repository provides a Flask web application for sentiment analysis using an NLP text classification model. It includes setup instructions for both Windows and macOS.

Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language generation.

A web-based AI-powered Sentiment Analyzer that uses VADER, ROBERTa and BERT models to detect positive, negative, or neutral sentiment in text. Built with Flask and NLP tools, it's perfect for ...

Abstract: In the text classification process, which is a sub-task of NLP, the preprocessing and indexing of the text has a direct determining effect on the performance for NLP models. When the studies ...