Insurance Premium Predictor Web App

This is a web app where a user can signup to the website first and then login to access the website. Then, he/she can give their age, select his/her gender (Male/Female), bmi, number of children, choose whether he/she is a smoker or not (Yes/No), and select his/her region (South-West, South-East, North-West, and North-East). After submitting all the six details, he/she can see the insurance premium plan amount that is required for him/her. This web app is made with HTML, BootStrap CSS Framework, and TailWind CSS Framework in the frontend, and Python Django framework in the backend. In the backend, six regression models are used - Linear Regression, Hist Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, Gradient Boosting Regressor, and Voting Regessor to make the best model where Gradient Boosting Regressor gives the best result with an accuracy of 89.798.