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Big Data Analysis with Revolution R Enterprise

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8 Hours14 Videos49 Exercises
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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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  1. 1

    Introduction

    Free

    Introduction 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.

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    Big Data Analytics Overview
    50 xp
    Challenges with Big Data
    50 xp
    Demonstration of Revolution R Enterprise for Big Data Analytics
    50 xp
    File Format
    50 xp
    Importing Data with rxImport Function
    100 xp
    Functions for Summarizing Data
    100 xp
    Creating New Variables using rxDataStep
    100 xp
    Transforming Variables Using rxDataStep
    100 xp
    Correlations
    100 xp
    Linear Regression
    100 xp
    How Parallel Exeternal Memory Algorithms in RevoScaleR work
    50 xp
    How the Algorithms in RevoScaleR work
    50 xp
  2. 2

    Data Exploration

    Free

    Intro 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.

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    Revolution Big Data - Data Exploration Session 1
    50 xp
    RevoScaleR options
    100 xp
    Import and Explore Dow Jones Data
    100 xp
    rxGetInfo Output
    50 xp
    Extracting meta data about a variable using rxGetVarInfo()
    100 xp
    Summarizing variables with rxSummary()
    100 xp
    Revolution Big Data - Data Exploration Session 2
    50 xp
    Exploring a Distribution with rxHistogram()
    100 xp
    Plotting bivariate relationships with rxLinePlot()
    100 xp
    Revolution Big Data - Data Exploration Session 3
    50 xp
    Summarzing Variables with rxCrossTabs()
    100 xp
    Summarzing Variables with rxCube()
    100 xp
  3. 3

    Data Manipulation

    Free

    Get introduced to the RevoScaleR functions used to manipulate and transform large datasets. Perform simple and complex transformations, and experiment with these via interactive exercises.

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    Revolution Big Data - Data Manipulation Session 1
    50 xp
    Concatenating Multiple Datasets to a Single .xdf file
    50 xp
    Converting From internal data.frame to external data.frame
    50 xp
    Using rxDataStep() to Transform Data
    100 xp
    Revolution Big Data - Data Manipulation Session 2
    50 xp
    More Complex Transforms Using transformFuncs
    100 xp
    Bad transformFunc functions
    50 xp
  4. 4

    Data Analysis

    Free

    Learn 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.

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    Data Preparation
    50 xp
    Preparing Data For Analysis: Import
    100 xp
    Preparing Data For Analysis: Exploration
    100 xp
    Linear Model
    50 xp
    Construct a linear model
    100 xp
    Prediction
    50 xp
    Generating Predictions and Residuals
    100 xp
    Compute Standard Errors
    50 xp
    Logistic Regression and the GLM
    50 xp
    Logistic Regression
    100 xp
    Individual Mortgage Information
    100 xp
    Higher Default Probability
    50 xp
    Individual Higher Default Probability
    50 xp
    Valid Arguments for rxGLM
    50 xp
    k Means
    50 xp
    Computing k Means with rxKmeans()
    100 xp
    Decision Trees
    50 xp
    Create some Decision Trees
    100 xp

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