Book Algorithms with
Julia
Algorithms with Julia is about the open-source programming
language Julia and about
optimization, machine learning, and differential equations.
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
Availability
Algorithms with Julia is available from
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): |i−j| > 1 instead of
|i−j| > 2.
- Page 330, second equation: replace e ⋅ ∇f by e ⋅ ∇f(r).
- Page 342: line 9: replace
exists'' byexist’’.
Feedback
I am in particular interested in any typos you may find and in
suggestions for material to be included in future editions.