A real-time Natural Language Processing (NLP) dashboard that classifies text sentiment using Machine Learning. This project marks a major milestone in my 100 Days of Data Science & ML journey, moving from a static notebook to a functional web application.
- Predictive Engine: Uses a Logistic Regression model trained on text data to classify sentiment as Positive or Negative.
- Interactive UI: Built with Streamlit for real-time user input and instant feedback.
- Confidence Metrics: Implements
predict_probato show the model's certainty percentage for every prediction. - Visual Analytics: Features a dynamic progress bar and metric cards for professional data visualization.
- Language: Python 3.x
- ML Libraries: Scikit-Learn, Joblib, Pandas
- Web Framework: Streamlit
- Version Control: Git Bash
To run this project on your local machine:
- Clone the repository:
git clone https://github.com/lagosboyyyyy/Sentiment-pro
- Install dependencies
pip install -r requirements.txt
- Launch the app:
streamlit run app.py