🎓 ML Model for Academic Purposes

An AI-powered academic chatbot designed to assist students with academic queries using NLP and sentence similarity techniques.

📋 Table of Contents

• Introduction
• ✨ Features
• ⚙️ Installation
• 🚀 Usage
• 📐 Model and Methodology
• 💻 Technologies Used
• 📁 Project Structure
• 🔮 Future Work
• 📜 License

Introduction

The ML Model for Academic Purposes chatbot is designed to provide real-time answers to students’ frequently asked academic questions. This project uses Sentence-BERT embeddings and cosine similarity to deliver the most relevant answer to a user's query.

✨ Features

• NLP-Powered: Understands academic questions through Sentence-BERT embeddings.
• High Precision Matching: Finds the best answer using cosine similarity.
• User-Friendly UI: Responsive web interface with Flask and HTML/CSS.
• Error Handling: Friendly messages when something goes wrong.

⚙️ Installation

Prerequisites

• Python 3.10 or higher 🐍
• Libraries listed in requirements.txt

Steps

1. Clone the repository

   git clone https://github.com/gyerra/AIML-PROJECT-2320040080.git
   cd AIML-PROJECT-2320040080
   

2.Install dependencies pip install -r requirements.txt

3.Dataset Place dataset.xlsx in the root directory

4.Run the app python app.py Open the chatbot at http://127.0.0.1:5000/ in your browser.

🚀 Usage Type your question in the chatbot's input field. Hit "Ask" to get your answer. View the response, or error if no match was found.

📐 Model and Methodology Sentence-BERT (all-MiniLM-L6-v2): Embeds student queries and compares them with each question in the dataset. Cosine Similarity: Measures similarity between the user query and dataset queries to find the best answer. Flask Backend: Routes user queries to the model and returns the results.

💻 Technologies Used Python: Core programming language. Pandas: Data processing. Sentence-Transformers: For Sentence-BERT embeddings. Flask: Web app framework. HTML/CSS: Frontend development.

🔮 Future Work Improve Accuracy: Test other models to enhance response accuracy. New Features: Add voice input, multilingual support, etc. Deployment: Make the chatbot publicly accessible for educational use.

📜License Licensed under the MIT License. See the LICENSE file for details.