MDSection 2 of 38 · 11 subtopics
Mathematics
The math behind neural networks: vectors, matrices, gradients, and the chain rule. Just the pieces that matter.
Learning path
Work through each subtopic in order. Click any file below to open its lesson. Track your progress with the checkbox at the bottom.
Subtopics
Each subtopic includes a concise explanation, code examples, and references.
01
Scalars
Number-line playground.
scalars
02
Vectors
2D vector canvas.
vectors
03
Matrices
Matrix grid with transformation canvas.
matrices
04
Dot Product
Two-vector angle visualizer.
dot-product
05
Norms
Distance visualization.
norms
06
Probability
Probability distribution playground.
probability
07
Sampling
Random sampling simulator.
sampling
08
Derivatives
Interactive function graph.
derivatives
09
Gradients
3D loss surface.
gradients
10
Chain Rule
Computational graph.
chain-rule
11
Gradient Descent
Loss landscape with moving parameter point.
gradient-descent