🧠 NLP Interactive Web App

An interactive NLP web application built with Streamlit, supporting tokenization, TF-IDF, word embeddings, POS tagging, and Named Entity Recognition.

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🎓 Learning Context

This project was developed during an NLP Bootcamp organized by the IT Department at KIET.

The core NLP concepts and implementations were demonstrated during the bootcamp sessions.
I implemented, structured, and deployed these concepts into an interactive Streamlit web application to reinforce my understanding.

This repository represents my hands-on practice and experimentation with foundational NLP techniques.

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🎥 Demo

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🚀 Features

• Tokenization (NLTK / spaCy)
• Stopword Removal
• Word Frequency Analysis
• Word Cloud Generation
• TF-IDF Vectorization
• Named Entity Recognition (spaCy / NLTK)
• Part-of-Speech Tagging

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🛠 Tech Stack

• Python
• Streamlit
• NLTK
• spaCy
• Scikit-learn
• Pandas
• Matplotlib
• WordCloud

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📁 Project Structure

nlp-web-app/
│
├── app.py                # Streamlit main app
├── requirements.txt      # Dependencies
├── assets/
│   └── demo.gif          # Demo recording
└── README.md

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⚙️ Installation

Clone the repository:

git clone https://github.com/VEERVS/NLP-Interactive-Web-App.git
cd NLP-Interactive-Web-App

Install dependencies:

pip install -r requirements.txt

Download spaCy model:

python -m spacy download en_core_web_sm

Run the app:

streamlit run app.py

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📌 Future Improvements

• Add Transformer-based models (BERT)
• Add text summarization
• Add chatbot functionality
• Improve UI/UX
• Deploy with Docker

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⭐ Support

If you find this project useful, consider giving it a star ⭐