Book 0
Apparatus
A reference volume, not a linear read. Books I to VII link into it; it links nowhere forward.
The problem it solves is narrow and real. A load-bearing chapter needs the reader to know what a Jacobian is, and teaching calculus inside the attention chapter destroys the attention chapter. So the fact moves here, gets a number, and the chapter cites it in one line.
Two rules keep it from becoming a textbook of its own. An entry is one screen, never more. And an entry that only one chapter needs does not belong here — it belongs in that chapter.
Nothing here is a gate. Start Book I today and follow the links when a step stops making sense.
47 entries · seven parts · nothing longer than one screen
- 0.LALinear Algebravectors, matrices, rank, eigen, SVD, norms, projections, the layout convention5 entries
- 0.MCMatrix Calculusgradients, Jacobians, the chain rule, the identity table, numerator layout8 entries
- 0.PRProbabilitydistributions, expectation, variance, Bayes, conditional independence6 entries
- 0.ITInformation Theoryentropy, cross-entropy, KL, mutual information, Jensen’s inequality5 entries
- 0.OPOptimisationconvexity, gradient descent, momentum, Lagrange multipliers, KKT5 entries
- 0.STStatisticsestimators, bias and variance, confidence intervals, tests, the bootstrap5 entries
- 0.NUNumericsfloating point, conditioning, stability, log-sum-exp, cancellation4 entries
- 0.GRGraph Theoryvertices and edges, representations, walks and connectivity, trees, traversal, shortest paths, Eulerian paths, complexity, centrality9 entries
Most cited
Generated from what actually links here, not chosen. It is the most useful line on the page, because it says why a fact is worth learning.
- 0.ST.01 — Estimators, bias and variance21 citations
- 0.LA.03 — Inner products, norms and cosine similarity16 citations
- 0.PR.01 — Distributions, discrete and continuous13 citations
- 0.PR.04 — Bayes' rule11 citations
- 0.PR.03 — Variance and covariance10 citations
- 0.MC.03 — The chain rule9 citations