Mathematics
Singular Value Decomposition and Its Pseudoinverse for Data Science
Quick fact
The SVD of any matrix exists for any rectangular matrix, and its pseudoinverse (Moore-Penrose inverse) gives the least-squares solution to linear equations, which powers most regression and signal processing algorithms.
Why this is interesting
Ever wondered how a search engine ranks millions of pages or how Netflix predicts what you'll watch next? It often comes down to a simple matrix operation called the singular value decomposition—a tool that reveals the hidden structure in any dataset.