Linear Algebra Essentials (Vectors, Matrices)

Summary

Vectors and matrices are the data structures underneath almost every ML model — understanding matrix multiplication and dot products makes concepts like weights and embeddings click much faster later.

• 1Practice multiplying small matrices by hand before relying on a library.
• 2Learn what a dot product represents geometrically (a measure of similarity/alignment).
• 3Connect this to a dataset: rows and columns as a matrix, and what operations on it mean.