Muhammad Ahmad

I am an entry-level machine learning enthusiast with hands-on experience developing, evaluating, and deploying data-driven projects. I focus on bringing models from experimentation into production-ready web deployments to solve real-world problems.

My projects include a fake news classifier, a telco churn predictor, and customer segmentation using K-Means, where I implemented preprocessing, model comparison, and evaluation using appropriate metrics like accuracy, ROC-AUC, precision, recall, and F1-score.

I work primarily with Python for data analysis and machine learning, and use Next.js/React for deployment and web interfaces. I am comfortable with tools such as Pandas, NumPy, Scikit-Learn, XGBoost, TF-IDF vectorization, and visualization libraries to communicate insights effectively.

I hold a Software Engineering degree from FAST-NUCES (Lahore) and Coursera certifications in supervised and advanced machine learning topics. I am motivated to contribute to data science or ML teams that value measurable impact and end-to-end ownership.