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Introduction to Computation and Programming Using Python

Introduction to Computation and Programming Using Python
作者:John V. Guttag
副标题:Revised and expanded edition
出版社:The MIT Press
出版年:2013-07
ISBN:9780262525008
行业:计算机
浏览数:52

内容简介

This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

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作者简介

作者简介:

John V. Guttag

1999年至2004年任麻省理工学院电气工程与计算机科学系主任(此前担任了5年的副主任)。Guttag教授目前是计算机科学与人工智能实验室网络及移动系统组的联合负责人。此外,他还进行软件工程、机器定理证明、硬件验证等领域的研究以及培训工作,并出版过相关主题的图书。Guttag教授获得美国布朗大学英语专业学士学位、应用数学硕士学位,获得多伦多大学计算机科学博士学位。

译者简介:

梁杰

北京航空航天大学计算机科学与技术专业大四学生。热爱开源、JavaScript、Python,喜欢做各种各样有趣的事情。

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目录

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读书文摘

务必记住,最高效的算法不一定是最合适的算法。 通常来说,最高效的算法都很难理解。 一种比较好的解决策略是:首先找到最简单直接的解决方法,然后通过找到它的计算瓶颈,接着想办法提高和瓶颈相关的代码的计算复杂度,从而提高性能。

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