path II · Mathematics
Mathematics
From 'what a proof is' to deriving a gradient and a learning algorithm. Every idea implemented in code, so none of it stays abstract.
0/10 subjects · each a complete document + a project
- 01Logic & the Art of Proofsoon
Why something is always true; and, or, not, all, some
- 02Sets, Functions & Inductionsoon
The containers and mappings under all of math
- 03Number Theory & Countingsoon
gcd, modular arithmetic, primes, permutations, and combinations
- 04Linear Algebra I: Vectors & Matricessoon
Vectors, the dot product, and matrices as transformations
- 05Linear Algebra II: Eigenvalues & SVDsoon
Eigenvectors, diagonalization, and the decomposition behind all of data
- 06Calculus I: Change & the Derivativesoon
Limits, derivatives, and the chain rule
- 07Calculus II: Gradients & Optimizationsoon
Partial derivatives, the gradient, and gradient descent
- 08Probabilitysoon
Chance, Bayes, random variables, and distributions
- 09Statistics & Inferencesoon
Sampling, estimation, maximum likelihood, and regression
- 10Optimizationsoon
Convexity and the math of learning — the bridge to AI