https://github.com/krish57-bit/sentiment-analysis-using-bert
Sentiment analysis using NLP techniques and BERT Model
https://github.com/krish57-bit/sentiment-analysis-using-bert
matplotlib natural-language-processing nlp nltk numpy pandas seaborn sentiment-analysis
Last synced: about 2 months ago
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Sentiment analysis using NLP techniques and BERT Model
- Host: GitHub
- URL: https://github.com/krish57-bit/sentiment-analysis-using-bert
- Owner: krish57-bit
- Created: 2025-06-17T13:33:24.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-17T13:44:45.000Z (about 1 year ago)
- Last Synced: 2025-06-17T14:37:14.104Z (about 1 year ago)
- Topics: matplotlib, natural-language-processing, nlp, nltk, numpy, pandas, seaborn, sentiment-analysis
- Language: Jupyter Notebook
- Homepage:
- Size: 23.4 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🧠 Sentiment Analysis using BERT
This project performs sentiment analysis on customer reviews using the pre-trained BERT model from Hugging Face (`nlptown/bert-base-multilingual-uncased-sentiment`).
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## 📌 Overview
The model classifies reviews into sentiment categories (1 to 5 stars). Reviews are scraped from a website (Yelp) and passed through a fine-tuned multilingual BERT model to generate sentiment scores.
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## 🚀 Features
- ✅ Web scraping using BeautifulSoup
- ✅ Tokenization using HuggingFace Transformers
- ✅ Sentiment scoring using BERT
- ✅ DataFrame construction for visualization/analysis
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## 🛠️ Installation
Install all required packages using:
```bash
pip install -r requirements.txt