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.

0/50 done50 lessons · 10 weeks
Week 1

Logic & the Nature of Proof

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What truth and implication mean, and the three proof techniques everything else rests on.

Week 2

Sets, Functions & Induction

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The containers and mappings under all of math, and proving infinitely many things at once.

Week 3

Number Theory & Combinatorics

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gcd, modular arithmetic, primes, and how to count without listing.

Week 4

Linear Algebra I — Vectors & Space

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A vector is a list of numbers that is also an arrow. Span, independence, basis.

Week 5

Linear Algebra II — Matrices as Transformations

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A matrix is a function that moves space. Multiplication, inverse, determinant.

Week 6

Linear Algebra III — Eigen & Decomposition

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The directions a transform doesn't rotate, and the SVD behind all of data.

Week 7

Calculus I — Change & the Derivative

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Limits, the derivative from first principles, and the chain rule backprop is built on.

Week 8

Calculus II — Gradients & Optimization

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Partial derivatives, the gradient, and gradient descent — the engine of learning.

Week 9

Probability — Reasoning Under Uncertainty

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Events, Bayes, random variables, and why the bell curve is everywhere.

Week 10

Statistics & the Bridge to AI

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Estimation, maximum likelihood, and deriving your first learning algorithm.