Introduction to Computation and Programming Using Python (2/e)
作者:
John V. Guttag 出版社: The MIT Press 副标题: With Application to Understanding Data 出版年: 2016-8-12 页数: 472 定价: USD 45.00 装帧: Paperback ISBN: 9780262529624
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.
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 studen...
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.
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 (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters.
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. 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. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
作者简介
· · · · · ·
John V. Guttag is the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT.
It is possible to deceive students into thinking that they have learned how to program by having them complete a series of highly constrained "fill in the blank" programming problems. However, this does not prepare students for figuring out how to harness computational thinking to solve problems. (查看原文)
圆宝
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人民邮电出版社2015版
1 有用 豌豆黄 2017-09-19 22:15:03
MITx: 6.00.1x 对应教材。作者对CS整体的掌控太强，整本书可算雅俗共赏，入门者易学，老成者也有很多收获。老头用得文字也很活泼，信手拈来即是典故，真是高人
0 有用 BlaCk 2020-03-09 00:35:25
MITx: 6.00.1x & 6.00.2x
0 有用 灌县王契 2021-10-27 14:50:32
作者挺喜欢用括弧和注脚抖机灵，一副堪布雷奇左胶的形象跃然纸上。也许大学生喜欢这样的吧，但是中年人就觉得得啦快点讲重点！#人间悲剧之学python的中年人
0 有用 z 2022-11-12 00:28:35 北京
MIT羊毛真香
0 有用 文山鬼 2021-08-30 08:09:24
这本书不是教技法的，重在讲解实用python去实现目的。尤其后半部分的simulation，probability，须得对这些概念有初步的理解。个人觉得，本书适合有强烈应用目的的同学，而非单纯的coding初学者。plus后面一些sampling的概念讲得挺好的。