The common dilemma that haunts the average home buyer is what is the right property in the right market and at the right price point? It is very difficult for a home buyer to choose and without scientific research they cannot make an informed decision. The decision made by the customers is based on their short- term want while they overlook their long-term wants or they are confused between the end-user necessities. Properties prices are the one side of the face of economy, well priced properties are lure for both sellers and buyers. Well priced Properties are the best investment of the individuals. With the development in a city, hundreds of property dealings happen every day due to which property prices in cities are keep varying, making it difficult to predict the most accurate and exact price of the property at a time. This also creating a bad competition among property dealers because they used to manually calculate the prices, which all always results in irrelevant prices. Also make either buyer or seller disappointed.

To overcome this situation, undoubtedly there is a need for a Machine Learning model that can do better research on the subject which can help both the developers and the home buyers. The ML model can predict the property prices with the help of present data. It also can analyze the home buyer’s preferences for a location and the value that hold for him we have to make REGRESSSION model which can predict best outcome prices of the property.

For this we have to go through many phases like Data Extraction, Data Cleaning, Outlier Detection, Training and Testing of Model etc.

This model will satisfy the best need of Buyers and Sellers. And give a scientific reason for their properties prices.