Amar Jaiswal has completed
Big Data Analysis with Revolution R Enterprise
Start Course for Free8 hr
3,650 XP
Loved by learners at thousands of companies
Course Description
Revolution R Enterprise allows R users to process, visualize, and model terabyte-class data sets at a fraction of the time of legacy products without requiring expensive or specialized hardware. Introductory course for accomplished R users to experience the functionality of Revolution R Enterprise.
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Introduction
FreeIntroduction to the RevoScaleR package that ships with Revolution R Enterprise. We discuss the challenges associated with dealing with Big Data and how the functions and algorithms in RevoScaleR address them.
Big Data Analytics Overview50 xpChallenges with Big Data50 xpDemonstration of Revolution R Enterprise for Big Data Analytics50 xpFile Format50 xpImporting Data with rxImport Function100 xpFunctions for Summarizing Data100 xpCreating New Variables using rxDataStep100 xpTransforming Variables Using rxDataStep100 xpCorrelations100 xpLinear Regression100 xpHow Parallel Exeternal Memory Algorithms in RevoScaleR work50 xpHow the Algorithms in RevoScaleR work50 xp - 2
Data Exploration
FreeIntro to the RevoScaleR functions used to explore large datasets. Learn how to use these functions to summarize, cross-tabulate, and visualize variables in large datasets.
Revolution Big Data - Data Exploration Session 150 xpRevoScaleR options100 xpImport and Explore Dow Jones Data100 xprxGetInfo Output50 xpExtracting meta data about a variable using rxGetVarInfo()100 xpSummarizing variables with rxSummary()100 xpRevolution Big Data - Data Exploration Session 250 xpExploring a Distribution with rxHistogram()100 xpPlotting bivariate relationships with rxLinePlot()100 xpRevolution Big Data - Data Exploration Session 350 xpSummarzing Variables with rxCrossTabs()100 xpSummarzing Variables with rxCube()100 xp - 3
Data Manipulation
FreeGet introduced to the RevoScaleR functions used to manipulate and transform large datasets. Perform simple and complex transformations, and experiment with these via interactive exercises.
Revolution Big Data - Data Manipulation Session 150 xpConcatenating Multiple Datasets to a Single .xdf file50 xpConverting From internal data.frame to external data.frame50 xpUsing rxDataStep() to Transform Data100 xpRevolution Big Data - Data Manipulation Session 250 xpMore Complex Transforms Using transformFuncs100 xpBad transformFunc functions50 xp - 4
Data Analysis
FreeLearn about the RevoScaleR functions used to analyze large datasets. Use these functions to perform analyses such as linear and logistic regression, k-means clustering, and decision tree estimation.
Data Preparation50 xpPreparing Data For Analysis: Import100 xpPreparing Data For Analysis: Exploration100 xpLinear Model50 xpConstruct a linear model100 xpPrediction50 xpGenerating Predictions and Residuals100 xpCompute Standard Errors50 xpLogistic Regression and the GLM50 xpLogistic Regression100 xpIndividual Mortgage Information100 xpHigher Default Probability50 xpIndividual Higher Default Probability50 xpValid Arguments for rxGLM50 xpk Means50 xpComputing k Means with rxKmeans()100 xpDecision Trees50 xpCreate some Decision Trees100 xp
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