楼主: igs816
7742 77

[其他] R: Mining Spatial, Text, Web, and Social Media Data (True PDF)   [推广有奖]

已卖:261186份资源

泰斗

6%

还不是VIP/贵宾

-

威望
9
论坛币
1765561 个
通用积分
20494.2983
学术水平
2754 点
热心指数
3477 点
信用等级
2565 点
经验
485149 点
帖子
5457
精华
52
在线时间
3897 小时
注册时间
2007-8-6
最后登录
2025-12-5

高级学术勋章 特级学术勋章 高级信用勋章 特级信用勋章 高级热心勋章 特级热心勋章

楼主
igs816 在职认证  发表于 2017-7-30 16:00:04 |AI写论文

+2 论坛币
k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群
赵安豆老师微信:zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

感谢您参与论坛问题回答

经管之家送您两个论坛币!

+2 论坛币
OxuPtwsOISLbND6VIeqK9DxYk8Aypwhe.jpg
English | 2017 | ISBN: 178829081X | 651 Pages | True PDF | 22 MB
This Learning Path is for R developers who are looking to making a career in data analysis or data mining. Those who come across data mining problems of different complexities from web, text, numerical, political, and social media domains will find all information in this single learning path.

Data mining is the first step to understanding data and making sense of heaps of data. Properly mined data forms the basis of all data analysis and computing performed on it. This learning path will take you from the very basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining.

You will learn how to manipulate data with R using code snippets and how to mine frequent patterns, association, and correlation while working with R programs. You will discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on R Hadoop projects.

Now that you are comfortable with data mining with R, you will move on to implementing your knowledge with the help of end-to-end data mining projects. You will learn how to apply different mining concepts to various statistical and data applications in a wide range of fields. At this stage, you will be able to complete complex data mining cases and handle any issues you might encounter during projects.

After this, you will gain hands-on experience of generating insights from social media data. You will get detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data.

This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:

- Learning Data Mining with R by Bater Makhabel
- R Data Mining Blueprints by Pradeepta Mishra
- Social Media Mining with R by Nathan Danneman and Richard Heimann

本帖隐藏的内容

R - Mining Spatial, Text, Web, and Social Media Data.pdf (22.15 MB, 需要: 10 个论坛币)


二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

关键词:social media Spatial Social Media Mini

已有 1 人评分经验 收起 理由
zl89 + 60 精彩帖子

总评分: 经验 + 60   查看全部评分

本帖被以下文库推荐

沙发
ljx2000119(真实交易用户) 发表于 2017-7-30 16:15:07
看看,谢谢

藤椅
marcus10(未真实交易用户) 发表于 2017-7-30 16:24:55
支持,即使楼主不奖励我论坛币,我也支持你们!加油

板凳
jinyizhe282(真实交易用户) 发表于 2017-7-30 17:00:51
哈哈哈哈哈哈         

报纸
yazxf(真实交易用户) 发表于 2017-7-30 17:04:54
谢谢你的书!

地板
hjtoh(未真实交易用户) 发表于 2017-7-30 17:07:39 来自手机
igs816 发表于 2017-7-30 16:00
English | 2017 | ISBN: 178829081X | 651 Pages | True PDF | 22 MB
This Learning Path is for R deve ...
楼主的资源独一无二

7
qw789789(真实交易用户) 发表于 2017-7-30 17:18:55
R: Mining Spatial, Text, Web, and Social Media Data
THX

8
钱学森64(未真实交易用户) 发表于 2017-7-30 19:04:14
谢谢分享

9
blancheyaodushu(未真实交易用户) 发表于 2017-7-30 19:22:50
thank you so much

10
Nicolle(真实交易用户) 学生认证  发表于 2017-7-30 20:04:49
提示: 作者被禁止或删除 内容自动屏蔽

您需要登录后才可以回帖 登录 | 我要注册

本版微信群
加好友,备注jr
拉您进交流群
GMT+8, 2025-12-5 19:36