• Ms. D.Sai Sudha
• Mr. Dr P.Prathap Naidu

When seeking to purchase a new home, people are cautious with their spending plans and market research. The purpose of the article is to forecast house prices for those who do not own a home based on their financial resources and goals. It will be possible to estimate pricing by examining the aforementioned goods, fare ranges, and advancements. In the study, predictions are made using several regression approaches, such as Linear Regression and Decision Tree Regression, and valuable data is used to compute accuracy and R2 score values. All of the aforementioned strategies have been applied to a data set in order to anticipate house prices and determine which is the most effective. The goal of this article is to assist the seller in estimating the cost of selling a home. Perfectly and to assist individuals in determining the precise moment to start building a house.

Machine Learning Based House Price Prediction

"Machine Learning Based House Price Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.i43-i46, July-2023, Available :http://www.jetir.org/papers/JETIR2307807.pdf

"Machine Learning Based House Price Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppi43-i46, July-2023, Available at : http://www.jetir.org/papers/JETIR2307807.pdf