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Linear Algebra in Python - Home Linear Algebra in Python - Home
  • Preface
  • Prologue
  • Volume 0 — The Array and the Machine
    • 0.1 Arrays, Shapes, and Vectorization
    • 0.2 Floating-Point Reality and the Tolerance Habit
    • 0.3 Vectors: Geometry, Norms, and Inner Products
  • Volume I — Matrices, Elimination, and Subspaces
    • 1.1 Matrices as Linear Maps: Four Ways to Multiply
    • 1.2 Elimination, Pivoting, and A = LU
    • 1.3 Inverses, Rank, and A = CR
    • 1.4 The Four Fundamental Subspaces
    • 1.5 Vector Spaces, Bases, and Coordinates
    • 1.6 Linear Maps and Change of Basis
    • 1.7 Determinants, Volume, and Orientation
  • Volume II — Orthogonality and Least Squares
    • 2.1 Projections and the Normal Equations
    • 2.2 Gram–Schmidt, QR, Householder, and Givens
    • 2.3 Least Squares Four Ways
  • Afterword
  • Repository
  • Open issue

Index

By Raymond Amador

© Copyright 2026 · CC BY-NC-SA 4.0 (text) / MIT (code).