Paper Title
House Price Forecasting Using Supervised Learning

Abstract
The real estate market is a standout amongst the most focused regarding pricing and keeps fluctuating. It is one of the prime fields to apply the ideas of machine learning on how to enhance and foresee the costs with high accuracy. The objective of the paper is the prediction of the market value of a real estate property. This system helps find a starting price for a property based on the geographical variables. By breaking down past market patterns and value ranges, and coming advancements future costs will be anticipated. This examination means to predict house prices in Mumbai city with Decision tree regress or. It will help clients to put resources into a bequest without moving towards a broker. The result of this research proved that the Decision tree regress or gives an accuracy of 89%. Keywords - Decision tree regress or, machine learning.