This project performs sentiment analysis using NLP techniques. The model is currently under training with an accuracy of 66.7%.
- app.py: Application for sentiment analysis.
- trained.py: Script to train the model.
- trained.ipynb: Jupyter notebook for model training and testing.
- model.pkl: Trained sentiment analysis model.