https://github.com/arpan132002/sentiment-analysis-with-bert-google-play-reviews

This project implements sentiment analysis using BERT (Bidirectional Encoder Representations from Transformers), a state-of-the-art pre-trained language model developed by Google.
https://github.com/arpan132002/sentiment-analysis-with-bert-google-play-reviews

bert-model lstm nlp sentiment-analysis

Last synced: about 1 month ago
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This project implements sentiment analysis using BERT (Bidirectional Encoder Representations from Transformers), a state-of-the-art pre-trained language model developed by Google.

• Host: GitHub
• URL: https://github.com/arpan132002/sentiment-analysis-with-bert-google-play-reviews
• Owner: arpan132002
• Created: 2024-08-05T11:48:37.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-09T00:40:43.000Z (5 months ago)
• Last Synced: 2024-08-09T19:26:52.132Z (5 months ago)
• Topics: bert-model, lstm, nlp, sentiment-analysis
• Language: Jupyter Notebook
• Homepage:
• Size: 235 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Sentiment Analysis with BERT for Google Play Reviews

## Overview

This project implements sentiment analysis using BERT (Bidirectional Encoder Representations from Transformers), a state-of-the-art pre-trained language model developed by Google. The goal is to classify text into sentiment categories such as positive, negative, or neutral. 

## Dataset

We'll load the Google Play app reviews dataset

## Features

- **Preprocessing**: Includes tokenization and padding to prepare text data for BERT.

- **BERT Model**: Utilizes BERT for feature extraction and sentiment classification.

- **Fine-Tuning**: Implements fine-tuning of the BERT model on the sentiment analysis dataset.

- **Evaluation**: Provides evaluation metrics including accuracy, precision, recall, and F1-score.

## Acknowledgements

- **BERT Model**

- **Hugging Face Transformers**