Expand your Python skills by working with data structures and algorithms in a refreshing contextβthrough an eye-opening exploration of complexity science. Whether youβre an intermediate-level Python programmer or a student of computational modeling, youβll delve into examples of complex systems thro
Think Complexity: Complexity Science and Computational Modeling
β Scribed by Allen B. Downey
- Publisher
- O'Reilly Media
- Year
- 2012
- Tongue
- English
- Leaves
- 146
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Expand your Python skills by working with data structures and algorithms in a refreshing context - through an eye-opening exploration of complexity science. Whether you're an intermediate-level Python programmer or a student of computational modeling, you'll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations. You'll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise.
π SIMILAR VOLUMES
Enhances Python skills by working with data structures and algorithms and gives examples of complex systems using exercises, case studies, and simple explanations.
Complexity science uses computation to explore the physical and social sciences. In<i>Think Complexity</i>, you'll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics.<br /><br />Whether you're an intermediate-level Python programmer or a student
<p>Expand your Python skills by working with data structures and algorithms in a refreshing context—through an eye-opening exploration of complexity science. Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of
<p>This book contains a revised version of the dissertation the author wrote at the Department of Computer Science of the University of Chicago. The thesis was submitted to the Faculty of Physical Sciences in conformity with the requirements for the PhD degree in June 1999. It was honored with the 1