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63 changes: 48 additions & 15 deletions README.md
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### LilHomie - Housing Price Prediction Rapid Prototype
# 🏠 LilHomie – Predicting Housing Prices (Prototype)

### Author: [(EJ) Vivek Pandey](https://viveckh.com)
**Author:** [Vivek Pandey (EJ)](https://viveckh.com)
**Contact:** [anton.503.overload@gmail.com](mailto:anton.503.overload@gmail.com)

LilHomie is a rapid prototyping project that aims to generate housing appraisals to determine values of properties in the New York Tri-state Area.
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This repository contains all the associated work that has been done for the area which includes:
* Web Crawler to gather housing data
* Notebooks associated with data engineering, EDA, and ML Modeling
* Serverless API setup to make predictions off the serialized models
* Web App
## 📌 What is LilHomie?

### Future Enhancements
* Adding support to crawl and extract through remaining 3 property page formats in Trulia
* Spiders in Web Crawler to extract data from Zillow
* Speeding up the crawler with distributed spiders
* Feeding the ML model with data of properties across the US and making necessary adjustments based on new results, instead of the tri-states properties it is limited to (but this requires the above three enhancements to be done first)
**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.

### Questions?
Email the author at anton.503.overload@gmail.com
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## 🧰 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.

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## 🚧 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)

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## 💬 Got Questions?

Feel free to reach out at: **[anton.503.overload@gmail.com](mailto:anton.503.overload@gmail.com)**