Think Complexity : Complexity Science and Computational Modeling, 2/e (Paperback)
暫譯: 思考複雜性:複雜科學與計算模型,第2版(平裝本)
Allen Downey
- 出版商: O'Reilly
- 出版日期: 2018-08-28
- 定價: $1,750
- 售價: 8.0 折 $1,400
- 語言: 英文
- 頁數: 200
- 裝訂: Paperback
- ISBN: 1492040207
- ISBN-13: 9781492040200
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相關分類:
資訊科學
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相關翻譯:
Think Complexity|複雜性科學與計算模型設計, 2/e (Think Complexity : Complexity Science and Computational Modeling, 2/e) (繁中版)
複雜性思考:複雜性科學和計算模型(原書第2版) (簡中版)
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商品描述
Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you’ll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics.
Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations.
In this updated second edition, you will:
- Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform
- Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines
- Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata
- Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism
Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.
商品描述(中文翻譯)
複雜性科學利用計算來探索物理和社會科學。在Think Complexity中,您將使用圖形、細胞自動機和基於代理的模型來研究物理學、生物學和經濟學的主題。
無論您是中級的Python程式設計師還是計算建模的學生,您都將通過一系列的實作範例、練習、案例研究和易於理解的解釋深入探討複雜系統的例子。
在這個更新的第二版中,您將:
- 使用NumPy陣列和SciPy方法,包括基本的信號處理和快速傅立葉變換(Fast Fourier Transform)
- 研究複雜物理系統的抽象模型,包括冪律、分形、粉紅噪聲和圖靈機
- 獲得填滿啟動程式碼和解決方案的Jupyter筆記本,以幫助您重新實現和擴展複雜性中的原始實驗;以及計算模型,如Turmites、圖靈機和細胞自動機
- 探索科學哲學,包括科學法則的本質、理論選擇,以及現實主義和工具主義
作為Python計算建模課程的理想教材,Think Complexity也幫助自學者獲得他們可能不會接觸到的主題和想法的寶貴經驗。