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
##行文好清晰，還可以再看。我將所有有關復雜係統的東西放在“金融”這一列下，不知道自己何時纔能獲得那犀利的判斷力和明亮的慧眼。
評分##讀瞭第一/二章，感覺還不錯！
評分##泛讀
評分##version2 py代碼很詳實，especially for usage of matplotlib and numpy.
評分##行文好清晰，還可以再看。我將所有有關復雜係統的東西放在“金融”這一列下，不知道自己何時纔能獲得那犀利的判斷力和明亮的慧眼。
評分##讀瞭第一/二章，感覺還不錯！
評分##行文好清晰，還可以再看。我將所有有關復雜係統的東西放在“金融”這一列下，不知道自己何時纔能獲得那犀利的判斷力和明亮的慧眼。
評分##如果不是python就好瞭，很薄也很快餐
評分##應該早看之。
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