Housing Pulse AI

ML-Powered Real Estate Prediction

About This Project

Housing Pulse AI is a complete machine learning pipeline that scrapes, processes, and analyzes real estate data to predict property prices. Built a robust data collection system using BeautifulSoup, implemented advanced feature engineering including neighborhood analysis and temporal trends, and trained ensemble models (Random Forest, Gradient Boosting) achieving 85% prediction accuracy. The Flask application serves predictions through a RESTful API with caching for performance.

Key Highlights

• Built end-to-end ML pipeline from data collection to deployment
• Implemented ensemble models achieving 85% prediction accuracy
• Designed feature engineering pipeline with 30+ derived features
• Created automated web scraping system with error handling
• Optimized model inference for real-time predictions

Key Learnings

• Advanced machine learning techniques
• Data preprocessing and feature engineering
• Web scraping best practices
• Flask web development