Think Complexity: Complexity Science and Computational Modeling

Think Complexity: Complexity Science and Computational Modeling Details

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.

Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tables
Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines
Get starter code and solutions to help you re-implement and extend original experiments in complexity
Explore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topics
Examine case studies of complex systems submitted by students and readers

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Title:Think Complexity: Complexity Science and Computational Modeling
Edition Language:English
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    Think Complexity: Complexity Science and Computational Modeling Reviews

  • ????

    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 point...

  • Louis

    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 m...

  • ?Misericordia? ~ The Serendipity Aegis ~  ?????? ????

    Fantabulous intro to complexity made simple.Free online author's version:

  • Paco Nathan

    An empirical approach to understanding complexity, randomness, and "emergence" in general. Each chapter considers a different area of problems, providing clear hands-on examples that (in the second ed...

  • Kami Bee

    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-seemin...

  • M Sheik Uduman Ali

    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 Automat...

  • 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,...

  • Giovanni

    A quick and shallow run through some computational modeling topics. Not what I was looking for unfortunately....

  • m ko

    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 pres...

  • Neal Aggarwal

    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 ...