Denbegnaye AI

Linear Algebra is the language AI uses to "think."
→ Vectors — every word, image, or user becomes a list of numbers (an embedding)

→ Matrices — a neural network is just layers of matrices transforming your data

→ Dot Product — measures similarity (this is how "king" and "queen" end up close together)

→ Matrix Multiplication — the core operation running billions of times during inference

→ Eigenvectors/Eigenvalues — find the directions where data varies the most (used in PCA, dimensionality reduction)

→ SVD — decomposes any matrix into simpler pieces; powers recommendation systems and compression

If you understand vectors and matrices, you understand how AI sees the world — as numbers in space.

#AI #LinearAlgebra #MachineLearning #DataScience #LearnAI

1 month ago | [YT] | 3