Housing Price Predictor
Photo by Paul Kapischka on UnsplashThis project is my attempt to apply data science and machine learning techniques in real estate investment aspect. It was structured to follow a standard machine learning framework, which can be adopted and further developed for other projects, from splitting of train and test data, EDA, preprocessing, selection of evaluation metric, model training, hyperparameter tuning.
Using CatBoostRegressor with hyperparameter tuning, the predictor achieved Mean Absolute Percentage Error (MAPE) at around 9% on validation set.
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Alexandra Truong
Data Scientist
With 5-year experience in real estate investment and a Master in Data Science at the University of British Columbia, I am interested in applying data science techniques and real estate knowledge to solve meaningful problems.