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1 Book Algorithms with Julia

Algorithms with Julia is about the open-source programming language Julia and about optimization, machine learning, and differential equations.

1.1 Table of Contents

  • Front Matter, pages i–xxi
  • The Julia Language
    • Front Matter, pages 1–1
    • An Introduction to the Julia Language, pages 3–15
    • Functions, pages 17–37
    • Variables, Constants, Scopes, and Modules, pages 39–49
    • Built-in Data Structures, pages 51–77
    • User Defined Data Structures and the Type System, pages 79–98
    • Control Flow, pages 99–129
    • Macros, pages 131–152
    • Arrays and Linear Algebra, pages 153–226
  • Algorithms for Differential Equations
    • Front Matter, pages 227–227
    • Ordinary Differential Equations, pages 229–256
    • Partial-Differential Equations, pages 257–304
  • Algorithms for Optimization
    • Front Matter, pages 305–305
    • Global Optimization, pages 307–328
    • Local Optimization, pages 329–361
  • Algorithms for Machine Learning
    • Front Matter, pages 363–363
    • Neural Networks, pages 365–396
    • Bayesian Estimation, pages 397–431
  • Back Matter, pages 433–439

1.2 Availability

Algorithms with Julia is available from

1.3 Corrigenda

  • Page 290: x ≥ 0 instead of x ≥ 1, twice in the formulas for u(x,y) and $A(x, y).
  • Page 299, equation (10.38): |ij| > 1 instead of |ij| > 2.

1.4 Feedback

I am in particular interested in any typos you may find and in suggestions for material to be included in future editions.