$ show Visualize-ML/Book4_Power-of-Matrix
This repository is a comprehensive educational resource for linear algebra and matrix computations, serving as the companion code for the book "Book 4: The Power of Matrices" from the "Iris Flower Book" series. It contains Jupyter notebooks and Streamlit apps that visualize core concepts from vectors and matrices to eigenvalue decomposition, SVD, and data projections. The code is pedagogical, using synthetic data and the Iris dataset to illustrate mathematical ideas through interactive plots and heatmaps. It is not a production application or data pipeline but a teaching tool. The repository is well-organized by chapter, though code is duplicated across notebooks rather than modularized, reflecting its educational nature.
The LLM identified 2 files worth highlighting for reuse:
Custom svd() function that wraps np.linalg.svd with configurable rounding precision and returns U, S, Vt in a consistent format. Also includes visualize_svd() for heatmap display. This pattern is self-contained and could be extracted as a reusable utility for any project needing consistent SVD output and visualization.
Streamlit app for interactive Lp norm visualization. Contains reusable distance functions fcn_Minkowski() and fcn_mahal() for computing Minkowski and Mahalanobis distances on a grid. These functions are parameterized and could be reused in other projects requiring distance calculations with custom norms.