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Machine Learning based House Price Prediction Model

In this digital era, People have become more aware on purchasing a new property. Many digital tools have been developed to analyze the property marketing strategies and the buyers' budget constraints. The goal of this paper is to predict house prices for non-home owners based on their financial resources and aspirations. Estimated prices will be calculated by using different tools such as Machine Learning (ML), Artificial Neural Network (ANN) and Chatbot. All of the above-mentioned techniques were used here to determine the most effective house price from the collected dataset. This research project will particularly conduct multiple researches on the affordability of houses present within Malaysia. The motive of this work is to build a prediction model to help in the process of house price prediction and assist both buyers and seller to have a general view on the current market price and trend.