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Math
Linear algebra, rebuilt
The geometric intuition behind vectors, matrices, and eigenstuff — without the textbook formalism.
8 lessons
~120 min total
Feynman
What you'll learn
See vectors, matrices, and determinants as geometric objects — not grids of numbers
Reason about eigenvectors and SVD without memorizing formulas
Connect linear algebra to ML, graphics, and data analysis with real intuition
Progress
0 / 8
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Lessons
1
What a vector really is
Beyond arrows and lists — a vector is anything that adds and scales.
3 objectives
2
Matrices as transformations
A matrix is a verb: a way to move space around.
3 objectives
3
The determinant, intuitively
How much a transformation stretches space — and why the sign flips.
3 objectives
4
Eigenvectors & eigenvalues
The directions a transformation leaves unchanged, only scaled.
3 objectives
5
Dot products & similarity
What "similar direction" means in any number of dimensions.
3 objectives
6
Changing bases
Same object, different coordinates — and why this is the heart of linear algebra.
3 objectives
7
Why least-squares works
Projecting onto the closest thing you can actually reach.
3 objectives
8
SVD — the fundamental theorem
Every matrix is a rotation, a stretch, and another rotation.
3 objectives
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