A website where user can get an estimate price of a house at certain places in Mumbai by entering certain requirements of the user.
The website is connected to a Machine Learning model that is trained on a dataset containing prices of different property all across Mumbai.
The website is a single page HTML coded frontend which is connected on the backend with the help of flask.
Components on the site:
- Location of the property (Drop-Down)
- Area in Sq/Ft (Input)
- No. of Bedrooms (Input)
- Toggle Buttons
- Gymnasium
- Car Parking
- Indoor Games
- Jogging Track
The model has been trained on the dataset "Housing Prices in Mumbai". The training algorithm in use is RandomForestRegresson. The dataset was broken into 70/30 ratio with random state of 0.
The model has an R2_Score: 0.82
Following libraries are required:
- Sci-kit Learn (Sklearn)
- Pandas
- Flask
- Numpy
