ARKO-RentSmart is a web application designed to predict rent prices based on a variety of highly correlated features such as property location, size, and amenities. The application is built using Python and Flask, with a machine learning model at its core to deliver accurate predictions.
- User-friendly interface for predicting rent prices
- Machine learning-powered model for rent prediction
- Interactive web-based platform using Flask
- Includes data visualization and analysis tools
- Integrated with Jupyter notebooks for real-time predictions
- Installation
- Usage
- Technologies Used
To set up the project locally, follow these steps:
Ensure you have the following installed on your system:
- Python 3.9
- Git
- Clone the repository:
git clone https://github.com/tobiakoko/ARKO-RentSmart.git
- Create and activate a virtual environment:
python3 -m venv venv source venv/bin/activate # For Windows use `venv\Scripts\activate`
- Install Dependencies:
pip install -r requirements.txt
- Usage:
To run the application locally:
flask run
- Flask: Web framework for Python
- Jinja2: Templating engine
- Pandas: Data manipulation and analysis
- Scikit-learn: Machine learning
- Seaborn/Matplotlib: Data visualization
- Jupyter: Interactive notebooks