作者:
Drew Conway
/
John Myles White 出版社: O'Reilly Media 副标题: Case Studies and Algorithms to Get You Started 出版年: 2012-2-22 页数: 324 定价: GBP 30.99 装帧: Paperback ISBN: 9781449303716
If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional m...
If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.
Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.
• Develop a naïve Bayesian classifier to determine if an email is spam, based only on its text
• Use linear regression to predict the number of page views for the top 1,000 websites
• Learn optimization techniques by attempting to break a simple letter cipher
• Compare and contrast U.S. Senators statistically, based on their voting records
• Build a “whom to follow” recommendation system from Twitter data
作者简介
· · · · · ·
Drew Conway is a PhD candidate in Politics at NYU. He studies international relations, conflict, and terrorism using the tools of mathematics, statistics, and computer science in an attempt to gain a deeper understanding of these phenomena. His academic curiosity is informed by his years as an analyst in the U.S. intelligence and defense communities.
Drew Conway is a PhD candidate in Politics at NYU. He studies international relations, conflict, and terrorism using the tools of mathematics, statistics, and computer science in an attempt to gain a deeper understanding of these phenomena. His academic curiosity is informed by his years as an analyst in the U.S. intelligence and defense communities.
John Myles White is a PhD candidate in Psychology at Princeton. He studies pattern recognition, decision-making, and economic behavior using behavioral methods and fMRI. He is particularly interested in anomalies of value assessment.
# Simply returns the full text of a given email message
# 获取邮件全部（每行）信息
msg.full <- function(path)
{
con <- file(path, open = "rt", encoding = "latin1")
msg <- readLines(con)
close(con)
return(msg)
}
# Retuns the email address of the sender for a given
# email message
# 获得邮件寄信人信息
get.from <- function(msg.vec)
{
from <- msg.vec[grepl("From: ", msg.vec)]
from <- strsplit(from, '[":<> ]')[[1]]
from <- from[which(from != "" & from != " ")]
return(from[grepl("@", from)][1])
}
# Retuns the subject string for a given email message
# 获得邮件主题
get.subject <- function(msg.vec)
{
subj <- msg.vec[grepl("Subject: ", msg.vec)]
if(length(subj) > 0)
{
return(strsplit(subj, "Subject: ")[[1]][2])
}
else
{
return("")
}
}
# Similar to the function from Chapter 3, this re... (查看原文)
Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data. With this book, you'll learn machine learning a...
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机械工业出版社2013版
涅瓦纳
0 有用 aeroliteminer 2013-09-24 17:33:34
用来熟悉R
0 有用 静远浮云 2012-05-12 22:32:14
当时学的时候痛不欲生的,现在又屁颠屁颠地自己找来看----我真是对自己无语了...
0 有用 SweeRoty 2014-06-14 15:54:13
非常实用的入门教程
0 有用 贝塔 2012-06-13 23:12:34
用R描述看着比较吃力
0 有用 Oneplus 2013-09-20 20:45:07
当成R入门回滚，其余没啥新鲜的了。
0 有用 ET民工 2019-01-21 20:26:53
读了中文版的书，现在好像应该用pyro更好一些吧？
0 有用 onnekas 2018-01-27 06:57:38
不错的入门书，有些code已经过时
0 有用 胡大善人 2017-02-04 11:12:51
对于曾经的我，这本苏帮助还是挺大的。 不过，仅此而已了。
0 有用 萨利 2016-04-17 09:01:38
跟machine learning没多大关系 属于data prepossessing吧 一般
0 有用 thali110 2016-02-06 11:36:53
data processing part可以看看 至于machine learning连个入门都嫌浅