House Price Prediction Model 🏠

📌 Introduction

This machine learning model predicts house prices using linear regression. It estimates prices based on input features like square footage, number of bedrooms, and location.

This dataset includes 1,000 homes, with the following features :

Size: The size of the house
Bedrooms: The number of bedrooms in the house
Bathrooms: The number of bathrooms in the house
Location: A feature representing the location of the house
YearBuilt: The year the house was built
RoofType: The type of roof on the house
Price: The price of the house

The goal is to understand how these factors influence a home’s value.

🚀 How to Use the Model

from huggingface_hub import hf_hub_download
import joblib

model_path = hf_hub_download(
    repo_id="sumeeh/house-price-prediction-LinearRegression",
    filename="House_Price_Prediction_LinearRegression.pkl"
)
model = joblib.load(model_path)