具體描述
Allen B. Downey擁有加州大學伯剋利分校的計算機科學博土學位和MIT的碩士與學土學位，現任美國歐林工程學院計算機科學係的教授，曾經在威爾斯利大學、科爾比學院和加州大學伯剋利分校教授計算機科學相關的課程。曾經擔任 Google的訪問科學傢，對復雜性科學和Python十分著迷，有較為深入的研究和豐富的實踐經驗。
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
##一本可以作為係統論、還原論等認知哲學的導讀讀物，看似薄薄的一本，拿到手還說定價這麼高虧瞭，結果一讀纔知裏麵彆有洞天。本書本身就是一個復雜性科學模型的範本——避免跨域細節，隻講所涉及問題域的知識點，乾淨利落。作者以python為基礎，演示瞭多種復雜係統的模型，...
評分##version2 py代碼很詳實，especially for usage of matplotlib and numpy.
評分 評分##:無
評分##讀瞭第一/二章，感覺還不錯！
評分 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。
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