Building Machine Learning solutions • Solving problems • Always learning
Computer Science student at Cairo University, specializing in Artificial Intelligence.
I focus on Machine Learning and AI Engineering, with a strong interest in building practical, end-to-end ML solutions — from data exploration and modeling to deployment.
Alongside AI, I practice competitive programming and problem solving, continuously strengthening my algorithms and data structures skills.
End-to-end Machine Learning project for predicting network throughput using real-world telecom data.
- Performed data analysis, preprocessing, feature engineering, and model evaluation
- Compared multiple regression models including Linear Regression, Random Forest, XGBoost, KNN, and SVR
- Improved XGBoost performance through hyperparameter tuning
- Built an interactive Streamlit application for model predictions and analysis
Tech: Python · Pandas · Scikit-learn · XGBoost · Streamlit
Machine Learning engineering work focused on building practical, interpretable ML solutions.
- Built and evaluated classification pipelines on real-world datasets
- Compared baseline approaches with Logistic Regression, Decision Trees, and Random Forest
- Worked on feature analysis, model interpretation, and leakage detection
- Documented experiments and results through reproducible notebooks
Tech: Python · Pandas · Scikit-learn · Jupyter
I actively practice competitive programming, focusing on algorithms, data structures, and efficient problem solving.
- Competitive Programmer on Codeforces
- Experience participating in ECPC
- Continuously improving my algorithmic thinking and problem-solving skills
