✨ Math Behind AI: A Linear Algebra Journey
A step-by-step exploration of the essential linear algebra concepts that power modern AI and machine learning. From vectors and matrices to eigenvalues, SVD, and optimization, this series is both my learning path and a shared guide for anyone who wants to understand the math that makes AI work.
Articles in this series
Tech Insights & Engineering Articles
Explore technical articles, software architecture deep dives, clean code tutorials, and computer science explorations from my journey.
Why Adding More Rows Doesn’t Always Add More Understanding
Different questions don’t always mean different answers.
The Hidden Geometry of Data — Understanding Column Space
When we learn linear algebra in school, we usually stop at plugging numbers into formulas.
Matrix Multiplication: The Hidden Engine Behind Machine Learning Predictions
Back in school, most of us learned **matrix multiplication** by crunching numbers on paper — multiply, add, move to the …
Ax = b: Understanding Linear Systems in Real Life and AI
In linear algebra, one of the most fundamental concepts is the equation: