Numerical Linear Algebra Explorer

• Project: Numerical Linear Algebra Explorer
• Focus: Numerical Analysis · Visualization · Sensitivity · Conditioning · Algorithm Intuition
• Live Demo: nla.woodygoodenough.com

Project Overview

This project is an interactive exploration of numerical linear algebra concepts that are foundational to machine learning and deep learning. The goal is to make key numerical ideas more intuitive through visualization, animation, and geometric interpretation rather than leaving them as purely symbolic formulas.

The site is especially motivated by the belief that strong mathematical understanding improves practical ML work. By visualizing how numerical behavior changes under perturbation and how algorithms evolve step by step, the project aims to build intuition that transfers to optimization, stability analysis, and high-dimensional generalization.

What the Project Explores

• Sensitivity and perturbation behavior visualized in 3D
• Conditioning and numerical stability through geometric examples
• Real-time progression of algorithms to show how iterative methods evolve
• Intuition-first explanations that connect low-dimensional visual cases to higher-dimensional ML practice

Why It Matters

Much of my machine learning work has involved exploring architectures, training strategies, and data augmentation, but I also intentionally spend time strengthening the mathematical side of that work. This project reflects that research-oriented side directly: it is about turning abstract numerical analysis into something visual, interactive, and easier to reason about.