People are careful when they are trying to buy a new house with their budgets and market strategies as well as sellers when they try to sell house because real estate is the least transparent industry in our ecosystem and the real estate market is a standout amongst the most focused regarding pricing and keeps fluctuating .Here, we intend to use Supervised Learning and various algorithms of Machine Learning such as Linear Regression, Lasso Regression, Decision Trees, etc. and conclude the most appropriate algorithm to use in such case and also the price prediction of house with best possible accuracy. House price prediction is an important topic of real estate. The literature attempts to derive useful knowledge from historical data of property markets.
Keywords: Real Estate, Predicting housing price, Supervised Learning, Machine Learning, Linear Regression, Lasso Regression, Decision Trees.
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL