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---
tags:
- regression
- house-prices
license: mit
model_name: House Price Prediction
library_name: joblib
language:
- en
---
# 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**
```python
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)
``` |