Twitter Sentiment Intelligence is a Streamlit-based NLP dashboard that performs real-time sentiment analysis on live or custom tweet inputs.
This project has been optimized and deployed as a production-ready Deloitte-style AI analytics app, using a custom sentiment classification model hosted on Hugging Face Hub.
It integrates a trained machine-learning pipeline to classify tweets as Positive, Negative, or Neutral, and displays confidence levels through interactive visualizations.
✅ Real-time tweet sentiment prediction (Positive / Neutral / Negative)
✅ Interactive analytics dashboard built with Streamlit
✅ Model deployed via Hugging Face Hub
✅ Seamless cloud deployment using Hugging Face Spaces
✅ Deloitte-ready business intelligence design — clean, minimal, and interpretable
✅ Customizable confidence thresholding and visualization charts
| Component | Technology Used |
|---|---|
| Frontend | Streamlit |
| Backend / Inference | scikit-learn, joblib, pandas, numpy |
| Model Hosting | Hugging Face Hub |
| Deployment | Hugging Face Spaces |
| Version Control | Git + Git LFS |
| Language | Python 3.11 |