Real Estate Cost Prediction is a property/home price predictor. Users can estimate the current housing values, as home prices rise by demand and are affected by location. This project focuses on house prices in Metropolitan areas. It mainly aims to provide a cost-effective system to estimate the cost of property within a few clicks.
Our project's motivation is to help users choose homes and real estate using our machine-learning model. This model, trained using a training dataset to provide the best accuracy based on the technique utilized, can be used to predict real estate values. Transparency and trust in the real estate industry are highly valued by most customers, particularly in Metropolitan areas.
The project aims to estimate real estate sale prices based on a range of economic factors and create an algorithm that can predict house values based on particular input features. We are using machine learning and artificial intelligence approaches.
- Clone the repository
git clone https://github.com/Sahil-Madhyan/Real-Estate-Price-Predictor.git- Navigate to the project directory
cd real-estate-cost-prediction- Install the required dependencies
pip install -r requirements.txt- Run the application
python main.pyEnter the required details about the property, such as location, area, age, etc., and the system will predict the estimated cost of the property.
Here are some screenshots of the application:
