This project analyses Bayut real-estate listings from Dubai, DIFC and Downtown to uncover pricing patterns, property characteristics and neighbourhood differences. After cleaning and structuring aggregated data, price per m² and key amenities were compared across districts. The analysis highlights market trends and provides insights useful for both buyers and investors.
This project builds a regression model that predicts the cost of producing industrial equipment. After cleaning the data and engineering meaningful features, several algorithms were evaluated. The final model helps the company estimate production expenses more accurately and plan budgets with greater confidence.
This project builds a machine-learning model that classifies user comments as toxic or non-toxic. After cleaning the text and converting it into numerical features with TF-IDF, several algorithms were tested and tuned. The final model helps online platforms flag harmful content automatically and maintain a safer communication environment.
This project builds a time-series model that forecasts hourly taxi orders for a service operating in a major city. After resampling data, creating lag features and adding rolling statistics, several models were evaluated. The final solution delivers accurate short-term forecasts and helps the company plan driver allocation during high-demand periods.
This project builds and compares several regression models to predict the price of used cars. After cleaning the listings data and engineering meaningful features, different algorithms — including tree-based models and gradient boosting — were evaluated for speed and accuracy. The final model delivers strong performance and provides a reliable baseline for car-valuation systems.
This project develops a secure data-transformation method that protects sensitive customer information while keeping model performance intact. A linear regression model was trained on the original data and then re-validated on data transformed with an invertible matrix. Identical R² scores confirmed that the transformation preserves predictive power while preventing reconstruction of personal data.
