This project aims to predict house prices in Bengaluru using machine learning techniques. The dataset used for this project is the Bengaluru Houses Price Dataset, which contains information on various attributes of houses in Bengaluru, such as location, size, number of bedrooms, and other features.
Data pre-processing was done using statistical imputation, one-hot encoding, and label encoding techniques to clean and process the data. Three different models were used for the prediction: Lasso, Decision Tree, and Linear Regression. The best accuracy achieved for the prediction was 87% using Linear Regression.
The project also includes a web app that has been deployed on Heroku, where users can input information about a house and get a predicted price for it based on the model. The app provides an interactive and user-friendly interface for users to get an estimate of house prices in Bengaluru.