This project is a Python-based system designed to detect duplicate questions on Stack Overflow. It utilizes advanced machine learning techniques, specifically Convolutional Neural Networks (CNN) combined with Natural Language Processing (NLP), to accurately identify semantically similar queries. The system features an interactive Flask-based web interface that allows users to easily submit questions for analysis, process multiple questions in batches, and train the model directly through the UI with progress tracking. It provides real-time predictions and displays detailed model performance statistics. For user convenience, sample questions from Stack Overflow are included, and the model can be trained in the background using threading to avoid UI blocking. Prerequisites include Python 3.7+, pip, and Git.

• Smart Duplicate Detection: Uses CNN-based NLP models to identify duplicate questions
• Web UI: Interactive Flask-based web interface for easy question submission and analysis
• Batch Processing: Submit and analyze multiple questions at once
• Model Training: Train the model directly from the web interface with progress tracking
• Real-time Predictions: Get instant results for your queries
• Model Statistics: View detailed model performance and training metrics
• Sample Questions: Try the model with pre-loaded sample questions from StackOverflow
• Background Training: Train the model without blocking the UI using threading