Course dossier
Learn each chapter, work through guided checkpoints, then test recall in the linked quiz.
Progress overview
Estimated quiz time: about 555 minutes, plus guided reading. Progress remains local to this browser.
Chapter learning paths
Advanced quiz on Hessians, curvature, convexity, momentum, Newton's method, conditioning, and finite-difference intuition.
Advanced quiz on chain rule applications, forward and backward passes, activations, softmax, and cross-entropy.
Foundational quiz on derivatives, partial derivatives, gradients, the chain rule, and convexity.
Advanced quiz on characteristic polynomials, eigendecomposition, symmetric matrices, quadratic forms, and spectral intuition used in ML.
Foundational quiz on gradient descent updates, learning rates, stochastic variants, loss functions, and regularization.
Advanced quiz on likelihoods, log-likelihoods, Bayes' rule, entropy, KL divergence, and probabilistic interpretations used in ML.
Advanced quiz on residuals, normal equations, design matrices, projections, and regularized linear regression.
Foundational quiz on linear maps, geometric effects of matrices, 2D rotations, and transformation properties.
Foundational quiz on matrix shapes, multiplication, transpose, determinants, inverses, rank, and solving linear systems.
Advanced quiz on centering, covariance matrices, principal components, projections, explained variance, whitening, and SVD connections.
Quiz on metric definitions, confusion matrices, composite scores, and ROC/PR evaluation based on the Performance Measures lecture outline.
Foundational quiz on expectation, variance, covariance, Gaussian distributions, conditional probability, Bayes' rule, and entropy.
Foundational quiz on vectors, norms, dot products, cosine similarity, orthogonality, and projections.