Abstract
Data Analytics and Machine Learning play an important role in extracting insights and patterns from datasets. The primary objective of using the above techniques for real world problems is to understand the intricacies of the problem, which is impossible with the help of manual human effort. The below chart shows the price trend (per sq. ft) over the past 10 years in Dubai, with a steady rise during the years from 2014. The 2020 pandemic plummeted the global prices due to the lack of demand and travel restrictions, which is clearly depicted in the chart. But at the very end towards 2022, the price is observed to be increasing steadily which shows the rise in demand due to the opening of travel and ease of restrictions across the globe.(UAE Residential Study, 2022). In this project, we leverage Data Analytics and Machine Learning to uncover some of the patterns and details about the house price trends in Dubai, and implement a prediction model using different machine learning techniques like Generalized Linear Model, SVM, Neural Networks etc.(Zhang, 2022). to predict the future prices of the properties in Dubai. Different models along with feature combinations would be tested to derive the optimal scores and model results along with different parameters to gauge model performance and results. It has been studied that feature combinations also impact model scores along with the variation of modeling techniques. (Dash, 1997)
Publication Date
2-2023
Document Type
Master's Project
Student Type
Graduate
Degree Name
Professional Studies (MS)
Department, Program, or Center
Graduate Programs & Research (Dubai)
Advisor
Sanjay Modak
Advisor/Committee Member
Hammou Messatfa
Recommended Citation
Alfalasi, Abdulla, "House Price Prediction Using Machine Learning Model" (2023). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/11613
Campus
RIT Dubai
