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🏠 LilHomie – Predicting Housing Prices (Prototype)

Author: Vivek Pandey (EJ) Contact: anton.503.overload@gmail.com


📌 What is LilHomie?

LilHomie is an early-stage project designed to predict the value of houses in the New York Tri-State Area (NY, NJ, CT). It brings together tools like web scraping, data science, machine learning, and web development to create a system that can estimate housing prices automatically.

This is a rapid prototype, meaning it’s a rough but working version built quickly to test ideas.


🧰 What’s Included in This Project?

This repo contains all the code and tools used in the project:

  • 🕷️ Web Crawler A custom-built tool that collects housing data from the internet (specifically from Trulia).

  • 📊 Notebooks Jupyter notebooks that:

    • Clean and prepare the data
    • Analyze trends
    • Train machine learning models to predict house prices
  • 🧠 Machine Learning Models Trained models that are saved and ready to use for making predictions.

  • 🌐 Serverless API A lightweight backend system that serves predictions from the ML models on-demand.

  • 💻 Web App A basic web interface where users can input property details and get a price estimate.


🚧 Future Plans

Here are some improvements planned for the next versions:

  • 🏗️ Add support for 3 more page formats on Trulia
  • 🏡 Add support to scrape housing data from Zillow
  • ⚡ Make the web crawler faster using distributed crawling (parallel spiders)
  • 🌎 Expand predictions beyond the NY tri-state area to cover the entire US (after improving the crawler)

💬 Got Questions?

Feel free to reach out at: anton.503.overload@gmail.com

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A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

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  • Jupyter Notebook 99.5%
  • Python 0.5%