Why do orthogonal matrices rotate while diagonal matrices stretch?
In this deep dive into linear algebra, we prove the geometric intuition behind the Singular Value Decomposition (SVD). By examining how inner products are preserved and how basis vectors are scaled, I demonstrate why linear transformations are restricted to these specific movements.
Master Spectral Decomposition. Learn how symmetric matrices are diagonalized into orthogonal eigenvectors and eigenvalues with clear geometric intuition.
Your Friendly Guide to the Math behind Data Science and AI 1 Introduction Matrix diagonalization is a crucial concept in linear algebra with tons of applications. Even more importantly, it is
The complete, friendly deep-dive into the core linear algebra every Data Scientist needs. 1 Introduction Have you ever wondered how to unlock the secrets hidden in data but felt overwhelmed
1 Introduction Linear transformations and Change of Basis are deceptively simple concepts that tempt us to rush over them quickly. But this shortcut is the perfect way to frustration. The
Mastering the Math Behind AI, Machine Learning and Data Science Introduction Matrix multiplication is the workhorse of the modern world. From powering deep learning algorithms to rendering photo-realistic graphics in video
