House-Price-Prediction-using-Machine-Learning

• The idea behind this project was to predict accurate price of a house with help of Machine Learning model. We built this Web Application where user can come and predict price of a house.
• User inputs like total number of bedrooms, bathrooms, sq. ft area, basement area, total floors etc are taken into consideration while predicting the price.
• Random Forest Algorithm is used to train the dataset and 88.3% accuracy is obtained.
• User can save their data of house prices by creating an account.

Tools and Technologies used:

1. Python and Django framework with MVT Architecture
2. SQLITE Database
3. HTML, CSS and JavaScript