Mahmoud A.

I am a Communication and Information Technology Engineer specializing in Machine Learning and Data Science, with hands-on experience in building intelligent systems and developing predictive models. I have a strong foundation in mathematics, algorithms, and programming, and I have implemented end-to-end machine learning pipelines including data preprocessing, feature engineering, model training, evaluation, and optimization. I developed a plant leaf disease classification system using Convolutional Neural Networks (CNNs), applying image preprocessing techniques and evaluating performance using accuracy, precision, recall, and confusion matrices. I have also implemented supervised learning algorithms such as Linear Regression, Logistic Regression, Decision Trees, and KNN, using cross-validation and hyperparameter tuning to improve performance. In addition, I perform data analysis and visualization using Pandas, NumPy, Matplotlib, and Seaborn to extract insights from data. I also have strong software development experience, including building a CPU Scheduling Simulator in C++, implementing the Banker's Algorithm, and developing a Python-based inventory system. My skills include Python, C++, Scikit-learn, TensorFlow/PyTorch, data structures, and Git. I am passionate about applying machine learning to solve real-world problems and building efficient, scalable solutions.