Students Professional
JA EN

#neural-network

2 articles

01 ·Deep Learning Basics·FREE·7 min read Neural Networks from Scratch — From One Neuron to Many Layers What a single neuron actually computes, and why stacking layers is pointless without an activation function — shown with a one-line proof that composing linear maps just gives you another linear map. Metaphor, math, an interactive figure, then fifteen lines of numpy. 02 ·Deep Learning Basics·★ MEMBER·9 min read Backpropagation from Scratch — It Is All Just the Chain Rule Why you can get gradients for ten million parameters for roughly the cost of one forward pass. The chain rule, computational graphs, a two-layer network worked by hand with real numbers, and where vanishing gradients come from — every symbol explained as it appears.