Think complexity: complexity science and computational modeling

✍ Scribed by Allen B. Downey

Publisher: O'Reilly Media
Year: 2012
Tongue: English
Category: Library

No coin nor oath required. For personal study only.

✦ 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,...

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