具体描述
Dive into Python's advanced possibilities, including algorithm analysis, graphs, scale-free networks, and cellular automata with this in-depth, hands-on guide. Whether you're an intermediate-level Python programmer, or a student of computational modeling, you'll examine data structures, complexity science, and other fascinating topics through a series of exercises, easy-to-understand explanations, and case studies. Think Complexity presents features that make Python such a simple and powerful language. Author Allen Downey provides code to help you get started, along with a solution for each exercise. With this book, you will: Work with graphs and graph algorithms, NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tables. Discover complexity science, the field that studies abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines. Explore the philosophy of science through the models and results in this book about the nature of scientific laws, theory choice, and realism and instrumentalism, and more.
用户评价
##应该早看之。
评分##书虽然薄，把相关资料都看下来也是不少的时间
评分本书的开源地址是：http://dou.bz/0ukGJy 这种书，图论写得不够清晰，复杂性部分最重要的进展没谈到，Python代码写得不够实用，该调用第三方库没调用。但，一个作者敢在一本小书里面将复杂性、网络分析、Python三个主题一块写，并开源，值得给个4分。属于复杂性研究入门参考好书。
评分##如果不是python就好了，很薄也很快餐
评分##泛读
评分##泛读
评分##书虽然薄，把相关资料都看下来也是不少的时间
评分##读了第一/二章，感觉还不错！
评分##泛读
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