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Big Data Predictive Analytics with Revolution R Enterprise - Revolution Analytics

Big Data Predictive Analytics with Revolution R Enterprise - Revolution Analytics
This special report from Datanami provides an in-depth view into a series of technical tools and capabilities that are powering the next generation of big data analytics. Used properly, these tools provide increased insight, the possibility for new discoveries, and the ability to make quantitative decisions based on actual operational intelligence. Examine these critical components of the big data analytics stack as individual layers: The platforms Analytics tools Required hardware

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SparkR by amplab-extras SparkR is an R package that provides a light-weight frontend to use Apache Spark from R. SparkR exposes the Spark API through the RDD class and allows users to interactively run jobs from the R shell on a cluster. NOTE: As of April 2015, SparkR has been officially merged into Apache Spark and is shipping in an upcoming release (1.4) due early summer 2015. R Data Import/Export Table of Contents This is a guide to importing and exporting data to and from R. This manual is for R, version 3.1.0 (2014-04-10). Copyright © 2000–2013 R Core Team Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one.

PSPP GNU PSPP is a program for statistical analysis of sampled data. It is a Free replacement for the proprietary program SPSS, and appears very similar to it with a few exceptions. The most important of these exceptions are, that there are no “time bombs”; your copy of PSPP will not “expire” or deliberately stop working in the future.

Example .  An example of nested downloads using RCurl. This example uses RCurl to download an HTML document and then collect the name of each link within that document. The purpose of the example is to illustrate how we can combine the RCurl package to download a document and use this directly within the XML (or HTML) parser without having the entire content of the document in memory. We start the download and pass a function to the xmlEventParse() function for processing. As that XML parser needs more input, it fetches more data from the HTTP response stream.

machine learning in Python "We use scikit-learn to support leading-edge basic research [...]" "I think it's the most well-designed ML package I've seen so far." "scikit-learn's ease-of-use, performance and overall variety of algorithms implemented has proved invaluable [...]." Testing Packages with Experimental R Devel Build for Windows · rwinlib/r-base Wiki Rtools 3.3 is in the process of being updated to use a new compiler toolchain produced by Jeroen Ooms based on GCC 4.9.3 and Mingw-W64 V3. The upcoming R 3.3 release is planning on adopting this new toolchain. Package authors using compiled code should test their packages with the new toolchain to ensure compatability. This document includes instructions for downloading the requisite versions of R, Rtools, and (optionally) RStudio to perform this testing. Step 1: Install R-devel-experimental for Windows

R Installation and Administration Table of Contents This is a guide to installation and administration for R. This manual is for R, version 3.1.0 (2014-04-10). Climate Charts & Graphs As a former Excel chart user, I want to help current Excel users make the transition to more advanced charting R with as little difficulty as possible. This post introduces my LearnR Toolkit to help Excel users move up to R in a systematic, step by step fashion. Introduction As an Excel chart user, I wanted to produce panel charts like this: After using VBA to build Excel panel charts (link), I knew I had to use a more advanced charting tool to continue my global warming, citizen climate science studies. R was the logical solution; I have made the switch to R and am now able to generate the types of charts I need to continue my citizen climate science efforts.

Hadoop Architect - All in 1 Combo Watch Module Sample recording for free .Try before you buy ! About the Course Hadoop designing, Hadoop development,Anayst,Admin,QA and Java-For-Mapreduce architecting Hadoop-based solutions for a global clientele. It lays emphasis on understanding what is Hadoop, how flow of data takes place in it and how it can enable storage and large-scale processing of big data along with deep dive into Hadoop ecosystem projects and Advacne administration like installation of single node cluster and Multi node cluster on ec2.

Integration of R, RStudio and Hadoop in a VirtualBox Cloudera Demo VM on Mac OS X Motivation I was inspired by Revolution’s blog and step-by-step tutorial from Jeffrey Breen on the set up of a local virtual instance of Hadoop with R. However, this tutorial describes the implementation using VMware’s application. One downside to using VMware is that it’s not free. I know most of the people including me like to hear the words open-source and free, especially when it is a smooth ride. VirtualBox offers an open-source alternative and thenceforth, I chose this. The Exploration of Statistical Software R ( έp n R ` ׾ I) Section: About R_note About the readers Who are interesting in this note? Where are they from? A record from google analytics shows the possible visits. 29,145 visits came from 5,195 cities and 144 countries (Jun 19, 2007 to Jun 19, 2011.)

RStudio, Revolution Analytics and Deducer: A Tale of Three GUIs I’m in the process of moving from SPSS to R at the moment. It’s not been the easiest of rides, but then learning how to do a core part of your job never really should be. It’s been fun, though – don’t get me wrong – it’s definitely been an adventure!! Here I’m going to review my (limited) experience with some of the GUIs available for R.