Mathematics for Machine Learning¶
Rebuild the foundations from scratch — not to memorize formulas, but to understand why the algorithms we use in machine learning look the way they do.
This is a multi-part tutorial series. Read the parts in order; later sections assume the ideas introduced earlier.
What you'll cover¶
- Part 1 — Algebra through logarithms: variables, equations, exponents, logarithms
- Coming soon: functions and linear models, then linear algebra, calculus, probability, and optimization
Parts¶
Part 1: Algebra through logarithms¶
Before neural networks or deep learning, we need a solid base in algebra, exponents, and logarithms — the same language used in loss functions and many model formulas.