具體描述
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.
用戶評價
##:無
評分##讀瞭第一/二章，感覺還不錯！
評分##爹，我的畢業大爹。迴歸正經書很好既可以當科普圖一樂也可以提高計算機編程水平，力薦
評分##書雖然薄，把相關資料都看下來也是不少的時間
評分##泛讀
評分##啥都帶一點，啥都不難。這種科普我最喜歡瞭。
評分##如果不是python就好瞭，很薄也很快餐
評分##version2 py代碼很詳實，especially for usage of matplotlib and numpy.
評分##應該早看之。
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