• Monika sahu
• Awantika Singh
• Rahul Chawda

House costs increase reliably, so there is a requirement for a system to expect house costs later on. House cost assumption can help the architect with choosing the selling cost of a house and can help the customer with organizing the ideal opportunity to purchase a house. Three factors sway the expense of a house which incorporates state of being, thought and region. .House price forecasting is a crucial topic of land. Machine learning techniques are applied to research historical property transactions in World to get useful models for house buyers and sellers. In the current, paper we examine all the expectation of future lodging costs that are produced by AI calculation. For the choice of forecast strategies we look at and investigate different expectation techniques. For the decision of expectation strategies we analyze and investigate different forecast techniques. We use regression as our model because of its versatility and probabilistic. Our outcome display that our methodology of the trouble had the chance to make progress, and can handle expectations that may be similar to other house cost forecast models. This paper intends to help the seller to appraise the selling cost of a house impeccably and to help individuals to anticipate the exact time slap to collect a house. We utilize Linear Regression strategies during this pathway, and our outcome isn't a sole assurance of one procedure rather it's the weighted mean of shifted methods to offer the most exact outcomes. The outcomes demonstrated that this methodology yields the least blunder and greatest precision than singular calculation applied.

House price prediction, Machine Learning, AI, Model, Linear Regression, Algorithm

"House price prediction using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.c710-c717, June-2021, Available :http://www.jetir.org/papers/JETIR2106370.pdf

"House price prediction using machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppc710-c717, June-2021, Available at : http://www.jetir.org/papers/JETIR2106370.pdf