Engineering writeups on artificial intelligence, computer vision, web architecture, and systems development.
Deep dive into developing a machine learning pipeline predicting academic performance from study habits, featuring data preprocessing, EDA, feature engineering, and regression diagnostics.
Comprehensive exploratory data analysis examining survival dynamics, imputation strategies for missing demographics, and multidimensional categorical encoding.
Transforming 5,000+ rows of raw transactional retail records into an automated multi-panel analytical report showing monthly revenue, category margins, and regional patterns.
Hands-on guide to foundational image transformations: grayscale conversion, Gaussian smoothing, Canny edge detection, and contour analysis on real-world test images.
Reflections on organizing AI/ML workshops, introducing generative AI tools like Google Gemini to 200+ students, and fostering a collaborative developer ecosystem.
Lessons from having 5+ pull requests merged during Hacktoberfest 2025, collaborating on public Python repositories, and earning verified status in ECWoc.