AI & Data30 min · Lesson 1 of 3
Linear Algebra & Gradients
The mathematical backbone of AI. Matrices, vectors, and how gradients drive backpropagation.
Linear Algebra in AI
Models are just vast collections of weights stored in matrices. To optimize them, we calculate gradients—the slope of the loss function—which tell us how to nudge weights to reduce error.
NumPy Vectorization
We use NumPy for high-performance array processing. Vectorized operations allow us to avoid slow Python loops, executing math in optimized C-code instead.