HummelsM/EduQuery

🎓 Educational Search Intent Classifier

An end-to-end NLP system that classifies student queries into learning intents to improve search and content delivery in educational platforms.

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🚀 Overview

This project builds a transformer-based text classification system that identifies the intent behind student queries, enabling adaptive routing of educational content.

🎯 Supported Intent Classes:

• CONCEPTUAL → Understanding concepts
• NAVIGATIONAL → Navigating resources
• PROCEDURAL → Step-by-step problem solving
• ADVANCED → Deep technical exploration

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🧠 Architecture

Data → Preprocessing → Transformer Model → Evaluation → Streamlit UI

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⚙️ Tech Stack

• Hugging Face Transformers
• PyTorch
• Scikit-learn
• Streamlit

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📊 Dataset

• Custom dataset (~560 samples)
• Manually labeled across 4 intent categories
• Balanced class distribution

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📈 Model

• Base model: DistilBERT
• Fine-tuned on domain-specific queries
• Evaluation metrics:
  • Accuracy
  • Precision / Recall / F1-score

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🔬 Key Features

• Custom dataset design for educational intent modeling
• Transformer fine-tuning pipeline
• Error analysis and performance optimization
• Interactive UI for real-time inference
• Intent-based recommendation system

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💻 Running the Project

1. Install dependencies

pip install -r requirements.txt