MML-09-04: Linear Transformations, Affine Mappings & Sums of Gaussians – Practice Quiz

Propagate Gaussian laws through linear and affine maps, combine Gaussian signals and noise, and construct samples from covariance factors. Analyze whitening, support rank, dependence assumptions, and nonlinear-layer failures. Normal-law notation uses variance or covariance as its second parameter.

35 questions combining single-select and multiselect formats, with worked explanations and feedback for every choice. Prerequisites: QS 9.3. Cognitive range: Tier 2–3. The local authored sequence progresses from accessible checks to computations, modeling diagnostics, and derivation recognition within that range.

Reference: Mathematics for Machine Learning, Chapter 6.