This project utilizes a Convolutional Neural Network (CNN) model trained on the IMDB dataset to analyze sentiment in movie reviews. The trained model is deployed using Flask for real-time web-based sentiment analysis.
The project leverages PyTorch for training a CNN model to classify movie reviews into positive or negative sentiments. It also employs Flask to deploy the trained model as a web application, enabling users to input movie reviews and receive sentiment predictions instantly.
- Training the Model: Execute
model.pyto train the CNN model on the IMDB dataset using PyTorch. - Running the Web Application: Start the Flask server by running
app.py. Access the sentiment analysis interface athttp://localhost:5000in your browser.
- Python 3.x
- PyTorch
- Flask
- NLTK
- pandas
- IMDB Dataset: [Keggle] (https://www.imdb.com/](https://www.kaggle.com/datasets/bhavikjikadara/imdb-dataset-sentiment-analysis))
This project is licensed under the MIT License. See the LICENSE file for more information.