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
##應該早看之。
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##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##《Think Python》引流過來的，是很淺顯的入門書，勝在廣而不勝在深，不過對於現階段的我很有用，一是入門瞭networkx，如果不是為瞭測試代碼我估計都不會去配置這個模塊，後續做瞭不少圖論的實驗，多個工具；二是啓發我結閤pagerank算法研究一個新的課題，現在開瞭個頭。練習沒有完全跟做，另外代碼部分有些錯誤，比較明顯。
評分##書雖然薄，把相關資料都看下來也是不少的時間
評分##:無
評分##書雖然薄，把相關資料都看下來也是不少的時間
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##應該早看之。
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