Matrix Math
Matrix math is a branch of linear algebra that deals with operations on matrices, which are rectangular arrays of numbers, symbols, or expressions arranged in rows and columns. It is fundamental for representing and manipulating data in fields like computer graphics, machine learning, physics simulations, and engineering. Key operations include addition, multiplication, transposition, and inversion, enabling transformations and computations in multi-dimensional spaces.
Developers should learn matrix math when working on applications involving 3D graphics, game development, data science, or robotics, as it provides the mathematical foundation for transformations, rotations, and scaling. It is essential for implementing algorithms in machine learning (e.g., neural networks) and computer vision, where data is often represented as matrices for efficient processing. Understanding matrix operations can optimize performance and accuracy in numerical computations.