Developed a Machine Learning-based Spam Email Classifier using Python and Scikit-learn to automatically classify messages as spam or legitimate (ham). Trained and evaluated the classification model using performance metrics such as accuracy, precision, recall, F1-score, and confusion matrix, achieving 90% test accuracy. This project strengthened my practical understanding of text classification, machine learning workflows, model evaluation, and Python development.

Developed a Machine Learning-based Handwritten Digit Recognizer using Python to identify and classify handwritten digits from 0–9. The project involved data preprocessing, model training, prediction, and performance evaluation. It provided practical experience in image classification, machine learning workflows, data handling, and model evaluation while strengthening my Python and AI/ML development skills.