Foundations
Convolutional Networks
Weight sharing over space: how machines learned to see.
You can jump straight in, but this star assumes Training & Optimization. Not recommended as a first stop.
Four layers of depth
Each layer ends with a quiz. Finish layer 4 and you own this concept.
- L1IntuitionWhy images need a different kind of layer than plain fully-connected networks, and what a convolution intuitively does.5m
40 XP - L2MechanicsThe mechanics of convolution, stride, padding, pooling, and how spatial dimensions shrink through a network.8m
70 XP - L3CodeImplementing a 2D convolution from scratch and building a small image classifier CNN in PyTorch.12m
110 XP - L4FoundationsThe math of discrete convolution, output-shape formulas, parameter counting, and translation equivariance.15m
180 XP
33 stars in the atlas.