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
##書雖然薄，把相關資料都看下來也是不少的時間
評分##應該早看之。
評分##:無
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##應該早看之。
評分##:無
評分##:無
評分本書的開源地址是：http://dou.bz/0ukGJy 這種書，圖論寫得不夠清晰，復雜性部分最重要的進展沒談到，Python代碼寫得不夠實用，該調用第三方庫沒調用。但，一個作者敢在一本小書裏麵將復雜性、網絡分析、Python三個主題一塊寫，並開源，值得給個4分。屬於復雜性研究入門參考好書。
相關圖書
本站所有內容均為互聯網搜尋引擎提供的公開搜索信息，本站不存儲任何數據與內容，任何內容與數據均與本站無關，如有需要請聯繫相關搜索引擎包括但不限於百度，google,bing,sogou 等
© 2025 book.qciss.net All Rights Reserved. 圖書大百科 版權所有