disponível para leitura em greenteapress.com/complexity2
- Ainda sem data definida...
Chapter 0 Preface
Complexity science is an interdisciplinary field — at the intersection of mathematics, computer science and natural science — that focuses on complex systems, which are systems with many interacting components.
One of the core tools of complexity science is discrete models, including networks and graphs, cellular automatons, and agent-based simulations. These tools are useful in the natural and social sciences, and sometimes in arts and humanities.
For an overview of complexity science, see http://thinkcomplex.com/complex.
[...]
0.1 Who is this book for?
The examples and supporting code for this book are in Python. You should know core Python and be familiar with its object-oriented features, specifically using and defining classes.
If you are not already familiar with Python, you might want to start with Think Python, which is appropriate for people who have never programmed before. If you have programming experience in another language, there are many good Python books to choose from, as well as online resources.
I use NumPy, SciPy, and NetworkX throughout the book. If you are familiar with these libraries already, that’s great, but I will also explain them when they appear.
I assume that the reader knows some mathematics: I use logarithms in several places, and vectors in one example. But that’s about it.
O clube de leitura Python não tem nehuma relação com a APyB mas seguimos o Código de conduta da Python Brasil. O time de resposta inicialmente será composto pelas pessoas mediadoras dos grupos.