Mohamed Khlaif

Ensured data integrity and consistency through data cleansing and distribution among different ministries following the division of the Ministry of Logistics, Transport, and Equipment. Implemented machine learning models to predict weekly business openings and closures, achieving a high accuracy rate of 93.4% and effectively forecasting daily authorization requests. Reduced false negatives by 20% through the development and deployment of advanced data cleaning techniques and predictive modeling, contributing to improved accuracy in monitoring ministerial activities. Technologies: Python, SQL, Data Cleaning Algorithms, Machine Learning (Scikit- Learn), Data Visualization (Seaborn, Matplotlib).