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https://github.com/hiresh9/sentiment-analysis

Sentiment Analysis is a natural language processing (NLP) technique used to determine the sentiment expressed in a piece of text. The goal is to analyze and categorize the emotions conveyed by the text, typically into categories such as positive, negative, or neutral. This process can help businesses understand customer opinions
https://github.com/hiresh9/sentiment-analysis

huggingface-transformers python roberta-model vader-sentiment-analysis

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Sentiment Analysis is a natural language processing (NLP) technique used to determine the sentiment expressed in a piece of text. The goal is to analyze and categorize the emotions conveyed by the text, typically into categories such as positive, negative, or neutral. This process can help businesses understand customer opinions

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# Sentiment Analysis with VADER, RoBERTa, and Transformers

This project provides a sentiment analysis tool that combines multiple models: VADER, RoBERTa, and Transformers, to analyze and classify text sentiment.

## Features

- **VADER Sentiment Analysis**: Uses VADER for basic sentiment scoring.
- **RoBERTa Sentiment Analysis**: Utilizes RoBERTa for advanced sentiment classification.
- **Transformers Integration**: Incorporates Hugging Face Transformers for additional model support.
- **Gradio Interface**: User-friendly web interface for sentiment analysis.

## Setup

1. **Clone the Repository**

```bash
git clone https://github.com/HiresH9/Sentiment-Analysis.git
cd sentiment-analysis