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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. There are three factors that influence the price of a house which includes physical conditions, concepts and location. The current framework includes estimating the price of houses without any expectations of market prices and cost increment. The objective of the paper is prediction of residential prices for the customers considering their financial plans and needs. 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 Linear Regression. It will help clients to put resources into a bequest without moving toward a broker. The result from this research proved linear regression gives minimum prediction error which is 0.3713.
Ghosalkar et al. (Wed,) studied this question.
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