Housing Price Prediction

This project implements a simple housing price prediction model using the California Housing dataset. It uses a linear regression model to predict housing prices based on various features.

Requirements

Ensure you have the following dependencies installed before running the project:

pip install numpy pandas scikit-learn

Dataset

The dataset used is the California Housing dataset, which is available in sklearn.datasets.

Usage

1. Clone the repository:

   git clone https://github.com/Brinda-93/house_price_prediction.git
   cd house_price_prediction

2. Run the script:

   python housing_price_prediction.py

Key Features

• Loads the California Housing dataset
• Splits the data into training and testing sets
• Trains a linear regression model
• Predicts housing prices
• Calculates the Mean Squared Error (MSE)

Output

The script prints the model coefficients and the Mean Squared Error for model evaluation.

Contributing

Feel free to submit pull requests for improvements or bug fixes.

License

This project is open-source and available under the MIT License.