House Price Prediction Project

Overview

This project aims to predict house prices using machine learning techniques. The primary focus is on developing a model to accurately predict house prices based on given features.

Project Structure

The project is organized as follows:

|- house_price_prediction
    |- data
    |- notebooks
    |- src
    |- README.md
    |- requirements.txt

• notebooks: Contains Jupyter notebooks, including the main prices.ipynb notebook.
• requirements.txt: Lists project dependencies.

Getting Started

1. Clone this repository:

   git clone https://github.com/your-username/house_price_prediction.git

2. Navigate to the project directory:

   cd house_price_prediction

3. Set up a virtual environment (optional but recommended):

   python -m venv venv

4. Activate the virtual environment:

   .\venv\Scripts\activate  # On Windows

5. Install project dependencies:

   pip install -r requirements.txt

6. Run the Jupyter notebook:

   jupyter notebook notebooks/prices.ipynb

Project Components

notebooks/prices.ipynb

• Main Jupyter notebook for exploring, analyzing, and predicting house prices.

Contributing

Feel free to contribute to the project by opening issues, suggesting improvements, or submitting pull requests.