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Think Complexity By: Allen B. Downey

Think Complexity - Complexity Science and Computational Modeling

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O'Reilly Media, February 2012

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.

  • 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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Preview added to your library

Think Complexity - Complexity Science and Computational Modeling

O'Reilly Media, February 2012
  • 1
  • 2
  • 3
  • 4
  • 5
( 1 customer rating)

eBook Information

Imprint: O'Reilly Media
ISBN: 9781449331696
Language:  English
Download options: EPUB (DRM-Free)

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