Machine Learning Based Real Estate Price Prediction

Based on machine learning, the cost of any home or apartment can be estimated. We can accomplish this utilizing test and training data derived from real-time data. We categorize and identify distinguishing characteristics appropriate for algorithms. We tested many algorithms, Decision Tree, Linear Regression, Random Forest Regression, etc. The work is appropriate for the general public, businesses buying real estate, and businesses selling real estate. It may be useful for administration, organizations, universities, to defend themselves against earthquakes and other natural disasters etc., for instance, in making judgments on effective allocation or establishing new facilities. Usually, there are a lot of people in line to purchase a new home or apartment. They can obtain a better estimate of how much they should prepare for. Along with helping the consumer prepare, it might lessen the likelihood that businesses would trick clients by offering expensive lodging. similar to how any seller may profit from a rough price point estimate. We were able to determine the top and lowest prices for every region in Bangladesh, including the District, Upazila, Thana, and Village. Our suggested housing price predicting algorithm has a 94% to 95% accuracy rate. It was a challenge for us.