Applied Econometrics With R

Applied Econometrics with R  eBooks & eLearning

Posted by ChrisRedfield at Aug. 13, 2014
Applied Econometrics with R

Christian Kleiber, ‎Achim Zeileis - Applied Econometrics with R
Published: 2008-09-30 | ISBN: 0387773169 | PDF | 222 pages | 4 MB

Learning Social Media Analytics with R  eBooks & eLearning

Posted by readerXXI at July 16, 2017
Learning Social Media Analytics with R

Learning Social Media Analytics with R
by Raghav Bali and Dipanjan Sarkar
English | 2017 | ISBN: 1787127524 | 394 Pages | True PDF | 12 MB

Mastering Parallel Programming with R  eBooks & eLearning

Posted by readerXXI at July 16, 2017
Mastering Parallel Programming with R

Mastering Parallel Programming with R
by Simon R. Chapple and Eilidh Troup
English | 2016 | ISBN: 1784394009 | 244 Pages | True PDF | 3.7 MB

Uncertainty Analysis of Experimental Data with R  eBooks & eLearning

Posted by AlenMiler at July 10, 2017
Uncertainty Analysis of Experimental Data with R

Uncertainty Analysis of Experimental Data with R by Benjamin David Shaw
English | 6 July 2017 | ASIN: B073RLXQW3 | 206 Pages | AZW3 | 5.09 MB

The New Statistics with R: An Introduction for Biologists [Repost]  eBooks & eLearning

Posted by ChrisRedfield at July 9, 2017
The New Statistics with R: An Introduction for Biologists [Repost]

Andy Hector - The New Statistics with R: An Introduction for Biologists
Published: 2015-03-15 | ISBN: 0198729057, 0198729065 | PDF | 208 pages | 33.73 MB

Manipulating data with R  eBooks & eLearning

Posted by hill0 at July 9, 2017
Manipulating data with R

Manipulating data with R by Valentina Porcu
English | 5 July 2017 | ASIN: B073R5ZBYQ | 299 Pages | AZW3 | 1.9 MB

Deep Dive into Statistical Modeling with R  eBooks & eLearning

Posted by naag at July 7, 2017
Deep Dive into Statistical Modeling with R

Deep Dive into Statistical Modeling with R
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 421 MB
Genre: eLearning | Language: English

R is a data analysis tool, graphical environment, and programming language. Without any prior experience in programming or statistical software, this video tutorial will help you quickly become a knowledgeable user of R. Now is the time to take control of your data and start producing superior statistical analysis with R.

Text Mining with R: A Tidy Approach  eBooks & eLearning

Posted by lengen at July 6, 2017
Text Mining with R: A Tidy Approach

Text Mining with R: A Tidy Approach by Julia Silge
English | July 2, 2017 | ISBN: 1491981652 | 179 Pages | PDF | 6 MB

Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.

XML and Web Technologies for Data Sciences with R [Repost]  eBooks & eLearning

Posted by ChrisRedfield at July 4, 2017
XML and Web Technologies for Data Sciences with R [Repost]

Deborah Nolan, Duncan Temple Lang - XML and Web Technologies for Data Sciences with R
Published: 2013-11-29 | ISBN: 1461478995 | PDF | 663 pages | 14.17 MB

Learning Social Media Analytics with R  eBooks & eLearning

Posted by lengen at July 3, 2017
Learning Social Media Analytics with R

Learning Social Media Analytics with R by Dipanjan Sarkar
English | May 26, 2017 | ISBN: 1787127524 | 423 Pages | PDF | 14 MB

Tap into the realm of social media and unleash the power of analytics for data-driven insights using R
About This Book
A practical guide written to help leverage the power of the R eco-system to extract, process, analyze, visualize and model social media data
Learn about data access, retrieval, cleaning, and curation methods for data originating from various social media platforms.
Visualize and analyze data from social media platforms to understand and model complex relationships using various concepts and techniques such as Sentiment Analysis, Topic Modeling, Text Summarization, Recommendation Systems, Social Network Analysis, Classification, and Clustering.