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Think Complexity

Complexity Science and Computational Modeling

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Description

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.

Reviews

On Apr 30 Grant van Staden wrote: A Textbook of Fundamental Topics
This was a difficult book to read! For the most part, it is a textbook introducing the field of Complexity Science and explaining some fundamental Computer Science topics. The explanations of the topics are not very different to the standard ones available in most other textbooks but the exercises provided are a bit more geared to practical use of the theory. Python is used to demonstrate some topics but don’t expect a lot of practical Python programming, the content is predominantly theoretical. Full Review  >

Rating: StarStarStarStarStar3.0

On Apr 27 Kiatikun Luangkesorn wrote:
Full Review  >

Rating: StarStarStarStarStar4.0

On Apr 23 Steven Jenkins wrote:
Full Review  >

Rating: StarStarStarStarStar4.0

On Apr 2 Michal Konrad Owsiak wrote: Challenging but rewarding
This one is not an easy one, however, if you won't be able to solve all the presented puzzles it is still worth getting through the book. Full Review  >

Rating: StarStarStarStarStar4.0

On Mar 30 Hitoshi Uchida wrote: Entry point of complexity theory
The author starts from introduction what the complexity theory is and why the specific problem can't be resolved with traditional approach precisely. After the introduction, it starts from basic algorithm explanation of graph, hash map, iterator, and how to estimate the calculation cost with sample codes and the concrete estimation procedure. Full Review  >

Rating: StarStarStarStarStar4.0

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