Prediction of House Price Using Machine Learn...

Prediction of House Price Using Machine Learning

Author Name : Ameya Bhawsar, Swaraj Kokare, Atharva Prabhu, Samarth Nanhore

ABSTRACT

The real estate market is one of the most price-sensitive and constantly changing. It is one of the key areas where machine learning principles are applied to improve and predict costs with high accuracy. The forecasting of a real estate property's market worth is the goal. Both buyers and sellers should be aware of housing price trends. But, it also represents the current economic climate. The number of bedrooms, location, floor number, and other criteria are only a few that influence house pricing. A neighborhood's house price may also increase if it is adjacent to major roadways, educational institutions, malls, and employment opportunities.In this work, Bangalore and Pune have been used as case studies. Our goal is to develop a model that can predict real-time property prices for various localities in and around Bangalore and Pune. Clients will be able to do this without turning to a broker and invest money in a bequest.

Keywords: Housing price prediction, gradient boosting, XG Boost.