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Titlebook: Beginning Data Science with R; Manas A. Pathak Book 2014 Springer International Publishing Switzerland 2014 Creating Tag Clouds.R Code.R I

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發(fā)表于 2025-3-21 19:14:44 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Beginning Data Science with R
影響因子2023Manas A. Pathak
視頻videohttp://file.papertrans.cn/183/182297/182297.mp4
發(fā)行地址Introduces fundamental data science methodologies using the R programming language.Covers concepts through real-world datasets and case studies.Examines cutting edge topics in both research and commer
圖書(shū)封面Titlebook: Beginning Data Science with R;  Manas A. Pathak Book 2014 Springer International Publishing Switzerland 2014 Creating Tag Clouds.R Code.R I
影響因子“We live in the age of data. In the last few years, the methodology of extracting insights from data or "data science" has emerged as a discipline in its own right. The R programming language has become one-stop solution for all types of data analysis. The growing popularity of R is due its statistical roots and a vast open source package library..The goal of “Beginning Data Science with R” is to introduce the readers to some of the useful data science techniques and their implementation with the R programming language. The book attempts to strike a balance between the how: specific processes and methodologies, and understanding the why: going over the intuition behind how a particular technique works, so that the reader can apply it to the problem at hand. This book will be useful for readers who are not familiar with statistics and the R programming language.
Pindex Book 2014
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發(fā)表于 2025-3-21 22:10:42 | 只看該作者
Data Visualization,at extracting information from visual cues, so a visual representation is usually more intuitive than a textual representation. Second, data visualization, for the most part, also involves a data summarization step; a visualization provides a concise snapshot of the data.
板凳
發(fā)表于 2025-3-22 00:48:16 | 只看該作者
Exploratory Data Analysis,he layout of the data first. Exploratory data analysis (EDA) is a collection of analysis techniques that we can apply to the data for this purpose. Most of these techniques are often simple to implement as well as computationally inexpensive, which allow us to obtain the exploratory results quickly.
地板
發(fā)表于 2025-3-22 05:41:01 | 只看該作者
5#
發(fā)表于 2025-3-22 09:29:54 | 只看該作者
Book 2014and methodologies, and understanding the why: going over the intuition behind how a particular technique works, so that the reader can apply it to the problem at hand. This book will be useful for readers who are not familiar with statistics and the R programming language.
6#
發(fā)表于 2025-3-22 14:58:14 | 只看該作者
ies.Examines cutting edge topics in both research and commer“We live in the age of data. In the last few years, the methodology of extracting insights from data or "data science" has emerged as a discipline in its own right. The R programming language has become one-stop solution for all types of da
7#
發(fā)表于 2025-3-22 19:17:59 | 只看該作者
Data Visualization,at extracting information from visual cues, so a visual representation is usually more intuitive than a textual representation. Second, data visualization, for the most part, also involves a data summarization step; a visualization provides a concise snapshot of the data.
8#
發(fā)表于 2025-3-22 22:03:33 | 只看該作者
Exploratory Data Analysis,he layout of the data first. Exploratory data analysis (EDA) is a collection of analysis techniques that we can apply to the data for this purpose. Most of these techniques are often simple to implement as well as computationally inexpensive, which allow us to obtain the exploratory results quickly.
9#
發(fā)表于 2025-3-23 04:44:23 | 只看該作者
https://doi.org/10.1007/978-3-319-12066-9Creating Tag Clouds; R Code; R Interfacing; R Programming; Social Network Data Analysis; Statistical Mode
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發(fā)表于 2025-3-23 09:29:50 | 只看該作者
978-3-319-37473-4Springer International Publishing Switzerland 2014
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