Pandas

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

Comment Moderation: Text Classification Model

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.

Projects

Taxi Service: Time-Series Demand Forecasting

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.

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.

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