Abstract: House price forecasting is an important topic of real estate. Machine learning techniques are applied to analyze historical property transactions to discover useful models for house buyers and sellers. Revealed is the high discrepancy between house prices in the most expensive and most affordable suburbs in the area. Significant time and expertise are needed to customize the model for a specific problem. A significant way to reduce the complicated design is by using Automated Machine Learning that can intelligently optimize the best pipeline suitable for a problem or dataset.

Keywords: House Price Prediction, Machine Learning, Google Oauth, Python.

PDF | DOI: 10.17148/IJARCCE.2022.11424

Open chat
Chat with IJARCCE