Data Solution · 2024
Mathematical Methods of AI
A grab-bag of mathematically-grounded AI work: Explainable AI, recommender systems, Kalman filters, and LDA topic modeling, built with a focus on interpretability.
A portfolio of small, mathematically rigorous AI projects: model-agnostic explainability methods, a Kalman filter implementation, LDA-based topic discovery on a text corpus, and a recommender experiment. Each piece prioritizes interpretability over raw accuracy.
Gallery
Selected screens.
