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Think Complexity
book

Think Complexity

by Allen B. Downey
March 2012
Beginner content levelBeginner
160 pages
4h 6m
English
O'Reilly Media, Inc.
Content preview from Think Complexity

Chapter 1. Complexity Science

What Is This Book About?

This book is about data structures and algorithms, intermediate programming in Python, computational modeling, and the philosophy of science.

Data structures and algorithms

A data structure is a collection of data elements organized in a way that supports particular operations. For example, a Python dictionary organizes key-value pairs in a way that provides fast mapping from keys to values, but mapping from values to keys is slower.

An algorithm is a mechanical process for performing a computation. Designing efficient programs often involves the co-evolution of data structures and the algorithms that use them. For example, in the first few chapters I present graphs, data structures that implement graphs, and graph algorithms based on those data structures.

Python programming

This book picks up where Think Python leaves off. I assume that you have read that book or have equivalent knowledge of Python. I try to emphasize fundamental ideas that apply to programming in many languages, but along the way you will learn some useful features that are specific to Python.

Computational modeling

A model is a simplified description of a system used for simulation or analysis. Computational models are designed to take advantage of cheap, fast computation.

Philosophy of science

The experiments and results in this book raise questions relevant to the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, ...

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Publisher Resources

ISBN: 9781449331672Errata