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Think Complexity: Complexity Science and Computational Modeling
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Think Complexity: Complexity Science and Computational Modeling

3.85  ·  Rating Details ·  148 Ratings  ·  11 Reviews
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 explanation ...more
Paperback, 160 pages
Published March 9th 2012 by O'Reilly Media (first published January 1st 2012)
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Apr 28, 2014 Muhammad rated it really liked it
Philosophy of science when it meets computer algorithms and software. The book is very mind opening, telling the reader that there is a land in human knowledge and thinking and research and just points towards this land. The book aims at asking questions more than answering them.

The only negative point about this book is that it tires to explain to someone who almost knows nothing about algorithms and data structures, so it spends some time explaining some basics like graph, and then moves to s
Apr 17, 2012 Louis rated it really liked it
Shelves: computer, math-stats
In operations research, among modelers it is a truism that models are for insights, not numbers. And the ability to provide insight is even more important than the ability to provide proofs that the model is correct or that the methodology is efficient or accurate. Think Complexity is an introduction to computational modeling for the purposes of finding this insight in areas that defy proof techniques.

Complexity science is an area that is easy to hype. I admit to being highly skeptical when a st
Apr 07, 2012 Kami rated it it was amazing
Shelves: research
A great read for anyone interested in Python or, more importantly, in how one might use Python or some other programming language to model such things as groups of agents exhibiting intelligent-seeming behaviour (my favourite), or fractals, or to use readily-available Python packages to easily construct competent graphs. Some not insignificant mathematical ability is required to fully appreciate some of what is discussed: manipulation of equations, logarithms and so on. However, I felt I still g ...more
m ko
Apr 03, 2012 m ko rated it really liked it
This one is not an easy one. Allen guides you through the various, complex, algorithms and data structures. This book is not for a beginners – you have to know Python already to solve exercises presented by author. The complexity of the book itself is also rather for slightly advanced developers. If you just start your journey with Python development it may be hard to follow.

What I liked, however, is the way Allen presents the material. He tries to show you different aspects of the development p
M Sheik Uduman Ali
Dec 18, 2013 M Sheik Uduman Ali rated it really liked it
It is almost 2 months for me to go through this book. Allen B Downey chooses 5 complex structures that we usually rely on third party libraries. These are: Graph, Scale-free Networks, Cellular Automata and fractals.

It is quite interesting to see complex algorithm explained using Python.

Allen started explaining what is Complex system with the example of how can you explain 'why planets are elliptical'. Interestingly he explained how people choose hard way with differential equation and another si
Franck Chauvel
I am disappointing by this book. I see it more like a study guide with a lot's of external resources to fetch and read (scientific publications or wikipedia articles) as well as programming exercises, and finally not much content. To give an example, the part about programming covering data structure and algorithm complexity is not related to complexity. Having already been programming, and having read a couple of books on the subjects such as Complex Adaptive Systems: An Introduction to Computa ...more
Neal Aggarwal
Jun 20, 2014 Neal Aggarwal rated it it was amazing
Fabulous book. The example code really gets driven home if you key it all in and struggle to understand the math. There is quite a bit of math here folks, remember that. All can be researched on-line though and the book extensively refers to Wikipedia which is fine for the likes of autodidacts like me.
Apr 11, 2014 Danny rated it really liked it
Good book! A programmatic tour of complexity.
Ray Pace
Mar 02, 2013 Ray Pace rated it liked it
I found it interesting for a quick thought about some complex problems addessed ina simple model.
Aug 03, 2015 Kaung rated it it was amazing
Covers python programming, computational modelling and philosophy of science.
Sergey Leschenko
Jun 26, 2012 Sergey Leschenko rated it it was ok
Nice idea, but I don't like the implementation.
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