Fares Ashraf

I’m an aspiring Machine Learning Engineer with a strong background in Python, data preprocessing, and supervised learning. One of my key achievements was developing a machine learning model to predict breast cancer diagnoses using the Wisconsin Breast Cancer dataset. I handled the full pipeline—data cleaning, feature selection, model training, and evaluation—and achieved over 95% accuracy using models like logistic regression and random forests. This project helped me deeply understand the importance of data quality, model selection, and evaluation metrics like precision and recall in sensitive domains like healthcare. What makes me unique is my end-to-end thinking—I don’t just stop at model building. I’m also learning about version control, deployment tools, and data engineering practices to prepare for real-world AI systems. I’m proactive, quick to learn new tools, and passionate about using AI to create practical and impactful solutions.