HOUSING PRICE PREDICTION THROUGH BIG DATA ANALYSIS IN CNN USING MACHINE LEARNING

HOUSING PRICE PREDICTION THROUGH BIG DATA ANALYSIS IN CNN USING MACHINE LEARNING

N. Seethalakshmi Karthikeyan*

* Civil Engineering, Rohini College of Engineering, Nagercoil

Abstract- Machine learning is a data analysis technique that automates the development of analytical models. It is a subfield of artificial intelligence that is founded on the premise that systems can learn from data, spot patterns, and make judgements. Housing prices have been one of the most concerning issues for individuals all over the world. The major goal of this research project is to forecast house prices using real-world factors. This study describes how to forecast housing costs using the CNN regression technique. Because home costs are inextricably linked to several criteria such as location, area, and car parking facilities, it takes all of this knowledge to estimate specific house prices.The proposed method takes into account the sophisticated factors employed in house price estimation and delivers a more accurate forecast. This article will also present an optimistic result for housing price projection for important cities in India, such as Chennai and Delhi.

Index Terms- Big Data Analysis, CNN, Machine learning