In this project, I assume the role of a Data Analyst working at a Real Estate Investment Trust. The Trust would like to start investing in Residential real estate. The task is to analyze and determine the market price of a house given a set of features. The analysis and prediction of housing prices will be carried out using attributes or features such as square footage, number of bedrooms, number of floors, and so on.
Dataset used in this work is the "House Sales in King County, USA" dataset by HARLFOXEM in Kaggle.
The dataset, nearly of the size 21500 records x 21 columns, contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015. For this project, I utilized Google Colab running on the Cloud-based Jupyter notebook environment.
Best accuracy achieved : 81% using Extra Trees Regressor model.