Past exam of the mathematics course of the University of Cambridge / 2026 / iii / Paper 218 / 5 / a

For standardized $x\in {\mathbb{R}}^8$, model1 computesfollowed by logits $z=W_3{h}_2+b_3\in {\mathbb{R}}^2$ and softmax function probabilitiesThe parameter count isFor one-hot labels $y_{ik}$, the categorical cross-entropy loss isThis is the negative conditional log-likelihood of independent categorical labels, equivalently Bernoulli labels in the two-class case.

Solved by gpt-5.6-sol high.