Price Prediction of House using KNN based Lasso and Ridge Model

Getting a house of our wishes within our budget in a residential area of our customization is quite a tedious process. In order to overcome this, we have developed a model to get a house of our interest with religious belief and budget this Implemented model is of linear regression and k nearest neighbor's algorithm with gradient descent optimization to make an optimal model for predicting house prices using the dataset. Performed feature engineering and selection using lasso and ridge penalties to eliminate features that had little or no impact on the residual sum of squares error. Then exposes Jupyter notebook cells as REST Endpoints to make predictions with new information. Finally, we are trying to send an email alert to the concerned user to give an alert of the house price