If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.
You'll work with a case study throughout the book to help you learn the entire data analysis process—from c...
If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.
You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.
Develop your understanding of probability and statistics by writing and testing code
Run experiments to test statistical behavior, such as generating samples from several distributions
Use simulations to understand concepts that are hard to grasp mathematically
Learn topics not usually covered in an introductory course, such as Bayesian estimation
Import data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics tools
Use statistical inference to answer questions about real-world data
作者简介
· · · · · ·
Allen Downey is an Associate Professor of Computer Science at the Olin College of Engineering. He has taught computer science at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master’s and Bachelor’s degrees from MIT.
Rails was a breath of fresh air to many developers exhausted by the “old ways”; Sinatra enters the arena with a similar game-changer: a beautifully minimalistic, “I’ll get out
of your way” approach. No generators, no complex folder hierarchies, and a brief yet
expressive syntax that maps closely to the functionality exposed by the Hypertext
Transfer Protocol verbs. (查看原文)
Thin continues this evolution by using code from Mongrel to parse HTTP
requests but improves network I/O performance via EventMachine, which manages
evented network communication. If Thin is not installed, Sinatra will first try to run
with Mongrel, choosing WEBrick if Mongrel isn’t available either. (查看原文)
>_<
chenge
Thyrlian
0 有用 脑洞少年浣熊君 2012-12-16 02:01:39
不夠好
0 有用 jeff 2012-09-30 17:01:14
放假没事翻翻，还是有点小收获的。。
0 有用 云kk 2012-02-11 23:50:15
一二章基本来自文档,看第三章不如直接去看rack spec,最后的例子懒得说了..也就第四章有点东西,一篇博客就能讲清楚的东西....
0 有用 低头路过 2014-11-16 02:13:13
读了后三章，似乎对读懂Sinatra源码又燃起希望了
0 有用 钢背哥 2011-12-25 13:53:31
五星推荐
0 有用 一〇八 2016-09-14 17:22:22
不算入门书，需要一定的web开发经验。
0 有用 低头路过 2014-11-16 02:13:13
读了后三章，似乎对读懂Sinatra源码又燃起希望了
0 有用 icemelon 2014-03-19 10:41:54
一般，没官网文档清楚
0 有用 中贰鹏 2014-01-01 20:20:46
读过jump start Sinatra后来读的这一本。相比之下这本书涵盖的原理性的内容更多一些，一个周末可以读完，值得推荐。不过写于2011，现在的Sinatra源码应该有很多更新了。回头得看看Sinatra的源码做update
0 有用 RoBeRt 2013-12-09 16:31:51
对于up and running来说 略晦涩了