In this project I have tried to do some EDA on the home price dataset and run different machine learning models to check which model gives the best solution with a good parameter. After getting the best model and saving it then I used Flask for deploying the model.
I took the dataset from here and the predicted prices of the houses are in Lakh (Hundred thousands)
- Python, HTML, CSS, JavaScript, jQuery
- Flask
git clone
https://github.com/Micky373/end_to_end_home_price_prediction_ml_project.git
cd end_to_end_home_price_prediction_ml_project
pip install -r requirements.txt
cd server
python sever.py
After the flask server is succesfully loaded go to the client directory and open the html
cd ../client
Then the UI will open
Here pass the location of the house, number of bed rooms, number of bath rooms and area then the prediction will be displayed
All the EDA, model training and predicting is clearly shown in the note books found in the
notebooks
folder
Contributions, issues, and feature requests are welcome!
Feel free to check the issues page.
Give a ⭐️ if you like this project!
- Special thanks to Dhaval Patel, who provided the tutorial for the house prediction model
- The UI implementation and code flow done with the help of this play list video