🏡 Housing Price Predictor(Boston)

A stylish and intelligent web application that predicts house prices in Boston using Linear Regression and a modern frontend built with Flask, HTML, CSS, and JavaScript.

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🔮 Features

• 📊 Linear Regression based ML model

• 🌐 Web app powered by Flask

• ✨ Clean, glassy, animated frontend with:

  • Home page with intro & button
  • Step-by-step feature input form
  • Beautiful result display page

• 🎯 Real-time price prediction

• 💥 Proper error handling for bad inputs

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📸 Screenshots

Page	Preview
🏠 Home Page
📝 Form Page
📈 Result Page

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🧠 Technologies Used

Area	Tech Stack
Machine Learning	Scikit-learn, NumPy, Pandas
Frontend	HTML5, CSS3, JavaScript (vanilla)
Backend	Python + Flask
Styling	Custom animations + glassmorphism
Model Saving	Pickle (.pkl files)

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📦 Installation Guide

# 1. Clone the repository
git clone https://github.com/codedbyasim/House-Price-Predection.git
cd House-Price-Predection

# 2. (Optional) Create a virtual environment
python -m venv venv
source venv/bin/activate  # for macOS/Linux
venv\Scripts\activate     # for Windows

# 3. Install dependencies
pip install -r requirements.txt

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🚀 Run the App

python app.py

Now open your browser and go to: http://localhost:5000

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📂 Folder Structure

├── app.py
├── linear_model.pkl
├── scaler.pkl
├── poly.pkl
├── requirements.txt
├── templates/
│   ├── home.html
│   ├── predict.html
│   └── result.html
├── static/
│   └── style.css
└── BostonHousing.csv

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🏗️ Dataset Info

We use the famous Boston Housing Dataset, which includes features like:

• Crime rate
• Land zoning
• Avg. rooms
• Distance to employment centers
• Tax, pupil-teacher ratio
• % of lower-income population, etc.

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👨‍💻 About the Developer

Asim Hanif A passionate Software Engineering student focused on solving real-world problems using Machine Learning and Web Development.

📬 Want to collaborate? Let’s connect!

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📜 License

MIT License — feel free to use, modify, or build on it.

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