Published Paper Details:

When dealing with real estate, whether you buy, sell or invest in real estate, you need a physical investigation. However, in this sudden pandemic situation, government regulations prevented the entire process mentioned above to be carried out. In our project, we want to help people who are planning to buy or sell a home or a particular property by informing them about the price range and safely planning the finances of the same home. In addition to forecasting real estate prices, it is also useful for real estate investors to know the trends in real estate prices at specific locations. Predict accurate prices based on statistical analysis comparisons and comparative market analysis with other similar properties, taking into account preliminary factors such as sale price, area quality, market, average property age, population area, address, etc. increase. This model uses machine learning techniques to curate them into ML models that can serve users. The buyer's main goal is to find a dream home with all the necessary equipment. Also, they look for these homes / properties with prices in mind, and there is no guarantee that they will get a product that is reasonably priced and not overpriced. Similarly, the seller is looking for a specific number to attach to the property as a price tag. Not only is this an exaggerated guess, but a lot of research is needed to complete the home assessment. This system helps you find the starting price of a property based on geographic variables. Future costs are expected by analyzing past market patterns and range of values, as well as future advances. The first thing that comes to mind when looking for a property is to contact various realtors. The problem with this is that the agent has to pay a small portion of the amount just to find a home and set a price for you. This model avoids such dangers and predicts accurate values. The main motivation for this model is to incorporate these machine learning techniques and curate them into an ML model that can serve users.