https://github.com/psycho-poodle/simple_rnn_imdb
This repository contains a simple web application for sentiment analysis of movie reviews using a pre-trained RNN model. The application is built with TensorFlow and Streamlit, making it easy to use and deploy.
https://github.com/psycho-poodle/simple_rnn_imdb
numpy python streamlit tensorflow
Last synced: 2 months ago
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This repository contains a simple web application for sentiment analysis of movie reviews using a pre-trained RNN model. The application is built with TensorFlow and Streamlit, making it easy to use and deploy.
- Host: GitHub
- URL: https://github.com/psycho-poodle/simple_rnn_imdb
- Owner: Psycho-Poodle
- Created: 2025-02-02T23:34:22.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-16T22:32:10.000Z (over 1 year ago)
- Last Synced: 2025-02-16T23:25:33.831Z (over 1 year ago)
- Topics: numpy, python, streamlit, tensorflow
- Language: Jupyter Notebook
- Homepage: https://simple-rnn-movie-review-prediction.streamlit.app/
- Size: 13.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# IMDB Movie Review Sentiment Analysis
This Project is a simple web application that uses a pre-trained Recurrent Neural Network (RNN) model to classify movie reviews from the IMDb dataset as either positive or negative. The application is built using TensorFlow for the machine learning model and Streamlit for the web interface.
## Features
- **Sentiment Analysis**: Classifies movie reviews as positive or negative.
- **User-Friendly Interface**: Built with Streamlit for easy interaction.
- **Pre-trained Model**: Uses a pre-trained(I have trained the model. The training file is in the same repo) RNN model for accurate predictions.
## How to Use
1. Clone the repository:
```bash
git clone https://github.com/Psycho-Poodle/simple_RNN_imdb
2. Navigate to the project directory:
```bash
cd simple_RNN_imdb
3. Install the required dependencies:
```bash
pip install -r requirements.txt
4. Run the Streamlit app:
```bash
streamlit run app.py
5.Open your browser and go to http://localhost:8501 to use the application.
## About the Model
The model used in this project is a simple RNN trained on the IMDb dataset. It uses a ReLU activation function and is capable of achieving good accuracy in sentiment classification tasks.
## Contact
For any questions or feedback, please reach out to bilalkhan31c7@gmail.com.