• Mohit S Amode
• S. R. Jadhav
• S. P. Dolli
• Pragati S Patil
• Mrunmai S Hiwarale

The Real estate market is one of the prime field for investment and with continuous development prices keep on fluctuating. In this paper, machine learning is used to accurately predict the value of the property based on different factors such as location, total area, number of bedrooms and number of bathrooms. Here, we have compared accuracy of three machine learning algorithm such as linear regression, lasso regression and ridge regression using the R-squared value. Based on the result, we used linear regression in our project to predict the value of the property in Pune City. The user will need to enter their requirements like location, total area, number of bedrooms and number of bathrooms in the application to get an idea of the price. This paper gives an idea on best suitable model for price prediction.

Machine Learning, Price Prediction, Linear Regression, Lasso Regression, Ridge Regression.

"Implementation of Linear Regression Algorithm In Machine Learning For Real Estate Price Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.503-506, August-2022, Available :http://www.jetir.org/papers/JETIRFP06089.pdf

"Implementation of Linear Regression Algorithm In Machine Learning For Real Estate Price Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. pp503-506, August-2022, Available at : http://www.jetir.org/papers/JETIRFP06089.pdf