Data Cleaning

Projects

Dubai Tenancy Lookup: Rental History & Property Insights

Dubai Tenancy Lookup is a Streamlit web app that lets users explore rental history and building details using their Ejari number. The tool aggregates open data from the Dubai Land Department, showing property information, past rental prices, building characteristics and location maps. It provides a clear overview of a unit’s rental trends and market context.

Projects

Real-Estate Market Insights for Dubai, DIFC & Downtown

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.

Projects

Industrial Cost Optimization with Regression Models

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.

Projects

Used Car Market: Price Forecasting

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.

Projects

Protecting Customer Data with Linear Transformation

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.

Projects

Modeling Gold Extraction Performance

This project builds a regression model that predicts the recovery rate of gold from raw ore during extraction and refinement. The analysis covers process parameters, intermediate outputs and final concentrate characteristics. The final model helps mining operations assess ore quality early and avoid launching unprofitable production cycles.

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